Programa de Pós-Graduação em Estatística

Produção Científica do Período de 2008 a 2025

Participação em eventos

Número total de items: 591

2025

  1. PINHEIRO, A. U-statistics: Foundations, Generalizations and Applications Part I. 2025.
    [ Google | Google Scholar ]
  2. PINHEIRO, A. U-statistics: Foundations, Generalizations and Applications. 2025.
    [ Google | Google Scholar ]
  3. MATOS, L. A. Modeling Longitudinal Data using Robust Mixed Models. 2025.
    [ Google | Google Scholar ]

2024

  1. SOUSA, A. R. S. Sobre a estimação Bayesiana de coeficientes de ondaletas em modelos de regressão não paramétrica com erros estacionários. 2024.
    [ Google | Google Scholar ]
  2. PINHEIRO, A. ANÁLISE ESPECTRAL APLICADA À DETECÇÃO DE MUDANÇAS EM SÉRIES DE IMAGENS SAR. 2024.
    [ Google | Google Scholar ]
  3. PINHEIRO, A. Time-referenced wavelet spatio-temporal change detection on multi-temporal SAR images. 2024.
    [ Google | Google Scholar ]
  4. AZEVEDO, C. L. N. Time series and multilevel modelling for longitudinal item response theory data. 2024.
    [ Google | Google Scholar ]
  5. AZEVEDO, C. L. N. Time series and Multilevel Modeling for Longitudinal Item Response Theory Data. 2024.
    [ Google | Google Scholar ]
  6. AZEVEDO, C. L. N. Time series and multilevel modeling for longitudinal item response theory data. 2024.
    [ Google | Google Scholar ]
  7. Trucios Maza, C. C. A new proposal to forecast highdimensional conditional covariance matrices via general dynamic factor models. 2024.
    [ Google | Google Scholar ]
  8. Lebensztayn, E. Limit theorems for a stochastic rumor process with multiple repetitions. 2024.
    [ Google | Google Scholar ]
  9. LUDWIG, G. A non-stationary spatio-temporal covariance model with advection effects for rainfall data. 2024.
    [ Google | Google Scholar ]
  10. NOBRE, J. S. A stochastic approximation ECME algorithm to semi-parametric scale mixtures of centred skew-normal regression models. 2024.
    [ Google | Google Scholar ]
  11. MATOS, L. A. Extending multivariate Student's-t semiparametric mixed models for longitudinal data with censored responses and heavy tails. 2024.
    [ Google | Google Scholar ]
  12. Rodrigues-Motta, M. Unsupervised Bayesian classification for models with functional covariates. 2024.
    [ Google | Google Scholar ]
  13. Rodrigues-Motta, M. Bayesian Analysis of Nonnegative Data Using Dependency-Extended Two-Part Models. 2024.
    [ Google | Google Scholar ]
  14. ZEVALLOS, Mauricio Forecasting VaR and ES through Markov Switching GARCH Models: Does the Specification Matter?. 2024.
    [ Google | Google Scholar ]
  15. ZEVALLOS, Mauricio Forecasting Realized Volatility: Does Anything Beat Linear Models?. 2024.
    [ Google | Google Scholar ]
  16. GARCIA, N. L. Correlated Functional Data. 2024.
    [ Google | Google Scholar ]
  17. GARCIA, N. L. Estatística e os Objetivos do Desenvolvimento Sustentável. 2024.
    [ Google | Google Scholar ]
  18. GARCIA, N. L. Desafios dos Programas de Pós-graduação em Estatística. 2024.
    [ Google | Google Scholar ]
  19. MAIA, R. P. Modelo de regressão t assimétrica Tipo II com efeitos aleatórios aplicado à análise longitudinal de desempenho acadêmico. 2024.
    [ Google | Google Scholar ]
  20. MAIA, R. P. Mesa; As trajetórias de egressos da política de permanência da UNICAMP. 2024.
    [ Google | Google Scholar ]
  21. MAIA, R. P. . 2024.
    [ Google | Google Scholar ]
  22. MAIA, R. P. Analisando dados de desempenho acadêmico o tempo de permanência via um modelo conjunto de dados longitudinais e de sobrevivência com tempo discreto. 2024.
    [ Google | Google Scholar ]
  23. MAIA, R. P. Perfil dos estudantes: Ensino Médio, ProFIS e Graduação. 2024.
    [ Google | Google Scholar ]
  24. DIAS, R. Bayesian Variable Selection for Function-on-Scalar Regression Models: a comparative analysis]{Bayesian Variable Selection for Function-on-Scalar Regression Models: a comparative analysis. 2024.
    [ Google | Google Scholar ]
  25. KIIHL, S. F. Modelagem Estatística: Uma jornada pelos TidyModels em R. 2024.
    [ Google | Google Scholar ]
  26. KIIHL, S. F. TidyModels in R with Malaria Data Application. 2024.
    [ Google | Google Scholar ]
  27. V. A. González-López The Efficient Determination Criterion for Partition Markov Model Estimation. 2024.
    [ Google | Google Scholar ]
  28. V. A. González-López Statistical Inference in Copula Models and Markov Processes IX (in ICNAAM 2024). 2024.
    [ Google | Google Scholar ]
  29. V. A. González-López STATISTICS AND DATA SCIENCE FROM WOMEN AROUND THE GLOBE. 2024.
    [ Google | Google Scholar ]
  30. SOUZA, V. F. Inference Tools for Markov Random Fields on Lattices: The R Package mrf2d. 2024.
    [ Google | Google Scholar ]
  31. SOUZA, V. F. Detecting Renewal States in Chains of Variable Length via Intrinsic Bayes Factors. 2024.
    [ Google | Google Scholar ]

2023

  1. SOUSA, A. R. S. . 2023.
    [ Google | Google Scholar ]
  2. SOUSA, A. R. S. A class of priors to perform asymmetric wavelet shrinkage. 2023.
    [ Google | Google Scholar ]
  3. SOUSA, A. R. S. A wavelet-based method in aggregated functional data analysis. 2023.
    [ Google | Google Scholar ]
  4. SOUSA, A. R. S. A wavelet-based method in aggregated functional data analysis. 2023.
    [ Google | Google Scholar ]
  5. PINHEIRO, A. Weighted U?statistics for absolutely regular processes with applications to time series and other dependent sequences. 2023.
    [ Google | Google Scholar ]
  6. PINHEIRO, A. Wavelet Feature Screening in High Dimensional Regression Model. 2023.
    [ Google | Google Scholar ]
  7. PINHEIRO, A. Wavelet spatio-temporal change detection on multitemporal SAR images. 2023.
    [ Google | Google Scholar ]
  8. CARVALHO, B. S. RNNR: distributed task execution system for scaling reproducible workflows. 2023.
    [ Google | Google Scholar ]
  9. CARVALHO, B. S. Revealing disease genetics: unveiling genetic architecture through differential copy number variation in admixed populations. 2023.
    [ Google | Google Scholar ]
  10. CARVALHO, B. S. RNNR: distributed task execution system for scaling reproducible workflows. 2023.
    [ Google | Google Scholar ]
  11. CARVALHO, B. S. Open Science in Brazil. 2023.
    [ Google | Google Scholar ]
  12. CARVALHO, B. S. Análise Federada de Dados Genômicos. 2023.
    [ Google | Google Scholar ]
  13. AZEVEDO, C. L. N. Um convite à Teoria da Resposta ao Item (TRI). 2023.
    [ Google | Google Scholar ]
  14. Trucios Maza, C. C. Forecasting risk measures in high-dimensional portfolios with additive outliers. 2023.
    [ Google | Google Scholar ]
  15. Trucios Maza, C. C. Forecasting Value-at-Risk and Expected Shortfall in Large Panels: A Robust General Dynamic Factor Approach.. 2023.
    [ Google | Google Scholar ]
  16. Trucios Maza, C. C. Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios. 2023.
    [ Google | Google Scholar ]
  17. Trucios Maza, C. C. Forecasting risk measures in high-dimensional portfolios. 2023.
    [ Google | Google Scholar ]
  18. PINHEIRO, H. P. Evaluating academic performance using nonparametric regression. 2023.
    [ Google | Google Scholar ]
  19. PINHEIRO, H. P. . 2023.
    [ Google | Google Scholar ]
  20. HOTTA, L. K. Session in Honor of Luiz Hotta. 2023.
    [ Google | Google Scholar ]
  21. HOTTA, L. K. Robust Estimation of Markov-Switching GARCH Model. 2023.
    [ Google | Google Scholar ]
  22. HOTTA, L. K. High-Dimensional Financial Time Series. 2023.
    [ Google | Google Scholar ]
  23. HOTTA, L. K. Robust Forecasting of Value-at-Risk and Expected Shortfall with Markov-Switching GARCH Models. 2023.
    [ Google | Google Scholar ]
  24. HOTTA, L. K. Forecasting VaR and ES through Markov Switching GARCH Models. 2023.
    [ Google | Google Scholar ]
  25. Rodrigues-Motta, M. Using complex models in the identication of sick cows. 2023.
    [ Google | Google Scholar ]
  26. ZEVALLOS, Mauricio Minimum Distance Estimation of Long-Memory Stochastic Duration Models. 2023.
    [ Google | Google Scholar ]
  27. ZEVALLOS, Mauricio Mortality in Peru during the COVID-19 pandemic: the role of high-altitude and population density. 2023.
    [ Google | Google Scholar ]
  28. ZEVALLOS, Mauricio Estimation and forecasting of Stochastic Volatility Models. 2023.
    [ Google | Google Scholar ]
  29. ZEVALLOS, Mauricio Minimum Distance Estimation of Long-Memory Stochastic Duration Models. 2023.
    [ Google | Google Scholar ]
  30. GARCIA, N. L. . 2023.
    [ Google | Google Scholar ]
  31. GARCIA, N. L. Unsupervise Bayesian classification for mixed regression models with applications to predicting illness for milking cows. 2023.
    [ Google | Google Scholar ]
  32. GARCIA, N. L. Mesa Redonda em Open Science. 2023.
    [ Google | Google Scholar ]
  33. GARCIA, N. L. A vida na Matemática. 2023.
    [ Google | Google Scholar ]
  34. GARCIA, N. L. Matemática Aplicada à Indústria. 2023.
    [ Google | Google Scholar ]
  35. MAIA, R. P. ?A inovação em tratamento de dados pessoais.?. 2023.
    [ Google | Google Scholar ]
  36. DIAS, R. Variational inference for Bayesian bridge regression. 2023.
    [ Google | Google Scholar ]
  37. DIAS, R. Variational inference for Bayesian bridge regression. 2023.
    [ Google | Google Scholar ]
  38. KIIHL, S. F. . 2023.
    [ Google | Google Scholar ]
  39. V. A. González-López A Metric Based on the EDC Criterion. 2023.
    [ Google | Google Scholar ]
  40. V. A. González-López Representation of the dependence among indicators arising from reservoirs/tailing dams breakout. 2023.
    [ Google | Google Scholar ]
  41. V. A. González-López Building a Metric through the Efficient Determination Criterion. 2023.
    [ Google | Google Scholar ]
  42. V. A. González-López Data Science and Statistics: Challenges and Opportunities in Latin America. 2023.
    [ Google | Google Scholar ]
  43. V. A. González-López Statistical Inference in Copula Models and Markov Processes VIII (in ICNAAM 2023). 2023.
    [ Google | Google Scholar ]
  44. SOUZA, V. F. Detecting renewal states in chains of variable length via intrinsic Bayes factors. 2023.
    [ Google | Google Scholar ]
  45. SOUZA, V. F. O Processo de Machine Learning. 2023.
    [ Google | Google Scholar ]

2022

  1. SOUSA, A. R. S. Kurtosis control in wavelet shrinkage with generalized secant hyperbolic prior. 2022.
    [ Google | Google Scholar ]
  2. SOUSA, A. R. S. Wavelet Shrinkage em Regressão Não Paramétrica. 2022.
    [ Google | Google Scholar ]
  3. CARVALHO, B. S. Applications of statistics in the biomedical field. 2022.
    [ Google | Google Scholar ]
  4. CARVALHO, B. S. A method to unveil the genetic architecture of diseases through differential copy number variation in an admixed population. 2022.
    [ Google | Google Scholar ]
  5. CARVALHO, B. S. ABE e a COVID-19: Ações e Desafios. 2022.
    [ Google | Google Scholar ]
  6. CARVALHO, B. S. How can CABANA become auto-suficient?. 2022.
    [ Google | Google Scholar ]
  7. Trucios Maza, C. C. Does portfolio resampling really improve out-of-sample performance? evidence from the Brazilian market.. 2022.
    [ Google | Google Scholar ]
  8. Trucios Maza, C. C. Risk Measures in Cryptocurrency Markets. 2022.
    [ Google | Google Scholar ]
  9. Trucios Maza, C. C. A Comparison of Methods for Forecasting Value-at-Risk and Expected Shortfall of Cryptocurrencies. 2022.
    [ Google | Google Scholar ]
  10. Trucios Maza, C. C. Forecasting Conditional Covariance Matrices in High- Dimentional Time Series: Implications for Portfolio Allocation. 2022.
    [ Google | Google Scholar ]
  11. Trucios Maza, C. C. Modelando series temporales financieras en alta dimensión. 2022.
    [ Google | Google Scholar ]
  12. Trucios Maza, C. C. Academia, mercado e otras cositas mas.. 2022.
    [ Google | Google Scholar ]
  13. vilca-Labra, F. E. Influence analysis and outlier tests for log-Birnbaum-Saunders regression models based on theEM algorithm. 2022.
    [ Google | Google Scholar ]
  14. vilca-Labra, F. E. Diagnostic analysis based on the EM algorithm: Application for Birnbaum-Saunders regression models ,.. 2022.
    [ Google | Google Scholar ]
  15. LUDWIG, G. Organização da Sessão: Estatística e Aprendizado de Máquinas. 2022.
    [ Google | Google Scholar ]
  16. LUDWIG, G. Minicurso MC2: Modelos geoestatísticos para fenômenos espaço-temporais. 2022.
    [ Google | Google Scholar ]
  17. LUDWIG, G. Bayesian Estimation and Variable Selection for Spatial Count Data with an Application to Rio de Janeiro Gun Violence. 2022.
    [ Google | Google Scholar ]
  18. PINHEIRO, H. P. . 2022.
    [ Google | Google Scholar ]
  19. PINHEIRO, H. P. The use of quasi U-statistics to test homogeneity of variants of coronavirus. 2022.
    [ Google | Google Scholar ]
  20. GUELLA, J. C. Recent theoretical results about Hilbert space embeddings of probabilities.. 2022.
    [ Google | Google Scholar ]
  21. GUELLA, J. C. SOME RECENT THEORETICAL RESULTS ABOUT HILBERT SPACE EMBEDDINGS OF PROBABILITIES. 2022.
    [ Google | Google Scholar ]
  22. MATOS, L. A. Estatística e Aprendizado de Máquinas. 2022.
    [ Google | Google Scholar ]
  23. MATOS, L. A. Tutorial: Modeling Longitudinal Data using Robust Mixed Models in R. 2022.
    [ Google | Google Scholar ]
  24. MATOS, L. A. Extending multivariate Student's-t semiparametric mixed models for longitudinal data with censored responses and heavy tails. 2022.
    [ Google | Google Scholar ]
  25. HOTTA, L. K. Robust estimation of high dimensional cDCC models. 2022.
    [ Google | Google Scholar ]
  26. Rodrigues-Motta, M. Unsupervised Bayesian classification for mixed regression models with scalar and functional covariates. 2022.
    [ Google | Google Scholar ]
  27. ZEVALLOS, Mauricio Minimum distance estimation of long-memory stochastic duration models. 2022.
    [ Google | Google Scholar ]
  28. GARCIA, N. L. Unsupervised Bayesian classification for mixed regression models with applications to predicting illness for milking cows. 2022.
    [ Google | Google Scholar ]
  29. GARCIA, N. L. Detecting Renewal States in Chains of Variable Length via Intrinsic Bayes Factors. 2022.
    [ Google | Google Scholar ]
  30. GARCIA, N. L. International Congress of Mathematics. 2022.
    [ Google | Google Scholar ]
  31. GARCIA, N. L. Inferência estatística para processos complexos. 2022.
    [ Google | Google Scholar ]
  32. GARCIA, N. L. Bayesian analysis of Brazilian and European written texts. 2022.
    [ Google | Google Scholar ]
  33. GARCIA, N. L. Bayesian analysis of Brazilian and European written texts. 2022.
    [ Google | Google Scholar ]
  34. GARCIA, N. L. Conversa com +1café. 2022.
    [ Google | Google Scholar ]
  35. MAIA, R. P. Modelo de regressão logística bivariado para estimar as chances de um candidato ao curso de Medicina ingressar em primeira chamada na Unicamp. 2022.
    [ Google | Google Scholar ]
  36. MAIA, R. P. Fórum Dez anos da Lei Federal de Cotas: história, dilemas e resultados - Sessão 2. Dados de ingresso. 2022.
    [ Google | Google Scholar ]
  37. DIAS, R. Adaptive Bayesian Selection of Basis Functions for Functional Data via Stochastic Penalization. 2022.
    [ Google | Google Scholar ]
  38. DIAS, R. Adaptive Bayesian Selection of Basis Functions for Functional Data via Stochastic Penalization. 2022.
    [ Google | Google Scholar ]
  39. KIIHL, S. F. . 2022.
    [ Google | Google Scholar ]
  40. Benaglia, T. Mixture models for longitudinal data of cognitive function in older adults. 2022.
    [ Google | Google Scholar ]
  41. V. A. González-López A Stochastic Characterization of Omicron Variant of SARS-COV 2 Virus. 2022.
    [ Google | Google Scholar ]
  42. V. A. González-López A Stochastic Characterization of Omicron Variant of SARS-COV 2 Virus. 2022.
    [ Google | Google Scholar ]
  43. V. A. González-López Statistical Inference in Copula Models and Markov Processes VII (in ICNAAM 2022). 2022.
    [ Google | Google Scholar ]

2021

  1. CARVALHO, B. S. End-to-End Implementations of GA4GH Standards at BIPMed. 2021.
    [ Google | Google Scholar ]
  2. CARVALHO, B. S. Desenvolvimentos da Iniciativa Brasileira em Medicina de Precisão. 2021.
    [ Google | Google Scholar ]
  3. vilca-Labra, F. E. A Robust Birnbaum-Saunders Regression Model based on asymmetric heavy-tailed distributions. 2021.
    [ Google | Google Scholar ]
  4. NOBRE, J. S. A new approach to modeling positive random variables with repeated measures. 2021.
    [ Google | Google Scholar ]
  5. HOTTA, L. K. Robust estimation of volatility models in the presence of additive outliers. 2021.
    [ Google | Google Scholar ]
  6. ZEVALLOS, Mauricio Estimation and forecasting of long memory stochastic volatility models. 2021.
    [ Google | Google Scholar ]
  7. GARCIA, N. L. Context tree selection and linguistic rhythm retrieval from written texts - Prêmio Johannes Kepler. 2021.
    [ Google | Google Scholar ]
  8. GARCIA, N. L. Interacting cluster point process model for epidermal nerve fibers. 2021.
    [ Google | Google Scholar ]
  9. GARCIA, N. L. SBMAC em Defesa da Ciência e Tecnologia. 2021.
    [ Google | Google Scholar ]
  10. MAIA, R. P. . 2021.
    [ Google | Google Scholar ]
  11. MAIA, R. P. . 2021.
    [ Google | Google Scholar ]
  12. KIIHL, S. F. . 2021.
    [ Google | Google Scholar ]
  13. KIIHL, S. F. . 2021.
    [ Google | Google Scholar ]
  14. KIIHL, S. F. . 2021.
    [ Google | Google Scholar ]
  15. V. A. González-López Covid-19 its Origins and Variants from a Stochastic Perspective. 2021.
    [ Google | Google Scholar ]
  16. V. A. González-López Language Modality Representation through Multiple Partition Markov Models. 2021.
    [ Google | Google Scholar ]
  17. V. A. González-López Language modality representation through multiple partition Markov models. 2021.
    [ Google | Google Scholar ]
  18. V. A. González-López Statistical Inference in Copula Models and Markov Processes VI ((in ICNAAM 2021). 2021.
    [ Google | Google Scholar ]

2020

  1. PINHEIRO, A. Nonparametric methods for detecting change in Multitemporal SAR/PolSAR Satellite Data. 2020.
    [ Google | Google Scholar ]
  2. CARVALHO, B. S. The Brazilian Initiative on Precision Medicine: Strategies and Findings - A glimpse into Global Bioinformatics Communities: Latin America. 2020.
    [ Google | Google Scholar ]
  3. CARVALHO, B. S. Advances by BIPMed. 2020.
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  4. CARVALHO, B. S. Computational Biology: new approaches to understand human diseases. 2020.
    [ Google | Google Scholar ]
  5. AZEVEDO, C. L. N. Time series and multilevel modeling for longitudinal item response theory data. 2020.
    [ Google | Google Scholar ]
  6. AZEVEDO, C. L. N. Time series and multilevel modeling for longitudinal item response theory data. 2020.
    [ Google | Google Scholar ]
  7. Lebensztayn, E. . 2020.
    [ Google | Google Scholar ]
  8. vilca-Labra, F. E. A lifetime distribution to model fatigue life on the Birnbam-Saunders distribution. 2020.
    [ Google | Google Scholar ]
  9. LUDWIG, G. Scalable modeling of nonstationary covariance functions with regularized B-spline deformations. 2020.
    [ Google | Google Scholar ]
  10. MATOS, L. A. A semiparametric mixed-effects model for censored longitudinal data. 2020.
    [ Google | Google Scholar ]
  11. Rodrigues-Motta, M. Using linear and non linear functional additive effects for predicting binary variables: an Baysian approach with an application to EEG data. 2020.
    [ Google | Google Scholar ]
  12. Rodrigues-Motta, M. A zero augmented Birbaum-Saunders mixed model with repeated measures: a Bayesian approach. 2020.
    [ Google | Google Scholar ]
  13. GARCIA, N. L. Filtering Textile Effects in Dyed Images Using Hidden Markov Random Fields. 2020.
    [ Google | Google Scholar ]
  14. GARCIA, N. L. Jobs in Brazil. 2020.
    [ Google | Google Scholar ]
  15. GARCIA, N. L. Interacting cluster point process model for epidermal nerve fibers. 2020.
    [ Google | Google Scholar ]
  16. MAIA, R. P. . 2020.
    [ Google | Google Scholar ]
  17. MAIA, R. P. . 2020.
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  18. MAIA, R. P. . 2020.
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  19. MAIA, R. P. . 2020.
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  20. MAIA, R. P. . 2020.
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  21. V. A. González-López Full Partition Markov Models. 2020.
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  22. V. A. González-López Americas Zika virus and its similarities with African and Asian lineages. 2020.
    [ Google | Google Scholar ]
  23. V. A. González-López Statistical Inference in Copula Models and Markov Processes V (in ICNAAM 2020). 2020.
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2019

  1. PINHEIRO, A. Wavelet estimation of the dimensionality of curve time series. 2019.
    [ Google | Google Scholar ]
  2. PINHEIRO, A. Wavelet estimation of the dimensionality of curve time series. 2019.
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  3. PINHEIRO, A. Wavelet estimation of the dimensionality of curve time series. 2019.
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  4. PINHEIRO, A. Wavelets, U-statistics and High Dimensional Data. 2019.
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  5. PINHEIRO, A. ALGUNS ASPECTOS TEORICOS E PRATICOS DA ANALISE ESTATISTICA DE DADOS DE ALTA DIMENSAO. 2019.
    [ Google | Google Scholar ]
  6. CARVALHO, B. S. Identificação de Variantes Raras em Estudos Genômicos. 2019.
    [ Google | Google Scholar ]
  7. CARVALHO, B. S. Perspectivas da Ciência Aberta no Brasil. 2019.
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  8. CARVALHO, B. S. New BIPMed Products. 2019.
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  9. AZEVEDO, C. L. N. Censored Linear Mixed Models based on the Birnbaum-Saunders distribution: Bayesian MCMC Implementation. 2019.
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  10. AZEVEDO, C. L. N. A new family of unidimensional item response models with asymmetric heavy tailed distributions and item response functions. 2019.
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  11. AZEVEDO, C. L. N. Censored Linear Mixed Models based on the Birnbaum-Saunders distribution: Bayesian MCMC Implementation. 2019.
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  12. AZEVEDO, C. L. N. Additive mixed models with time series structures. 2019.
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  13. GALLESCO, C. Soft local times and applications. 2019.
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  14. GALLESCO, C. Recent applications of soft local times. 2019.
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  15. Lebensztayn, E. Phase transition for the frog model on trees. 2019.
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  16. vilca-Labra, F. E. Birnbaum-Saunders Linear Mixed-Effects Models with Censored Data: Bayesian MCMCImplementation. 2019.
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  17. vilca-Labra, F. E. A robust multivariate Birnbaum-Saunders distribution: EM-estimation. 2019.
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  18. LUDWIG, G. Scalable modeling of nonstationary covariance functions with regularized B-spline deformations. 2019.
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  19. PINHEIRO, H. P. Bayesian mixture models for longitudinal data on cognition loss in elderly people. 2019.
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  20. PINHEIRO, H. P. Homogeneity tests for comparisons of groups of DNA sequences using U-statistics and substitution models. 2019.
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  21. GARCIA, J. E. Optimal Model for a Markov Chain with Markov Covariates. 2019.
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  22. GARCIA, J. E. Robust Minimal Markov Model. 2019.
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  23. GARCIA, J. E. Minimal Markov model for a set of Markov chains. 2019.
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  24. MATOS, L. A. Estimation and diagnostics for partially linear censored regression models based on heavy-tailed distributions. 2019.
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  25. MATOS, L. A. Estimation for partially linear censored regression models based on heavy tailed distributions. 2019.
    [ Google | Google Scholar ]
  26. MATOS, L. A. Longitudinal Models for Multiple Censored Responses Data. 2019.
    [ Google | Google Scholar ]
  27. MATOS, L. A. Flexible longitudinal linear mixed models for multiple censored responses data. 2019.
    [ Google | Google Scholar ]
  28. HOTTA, L. K. On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation and forecasting. 2019.
    [ Google | Google Scholar ]
  29. HOTTA, L. K. Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: a General Dynamic Factor Approach. 2019.
    [ Google | Google Scholar ]
  30. Rodrigues-Motta, M. Zero in ated and zero augmented mixed models. 2019.
    [ Google | Google Scholar ]
  31. ZEVALLOS, Mauricio Estimation of ARFIMA models: a minimum distance approach. 2019.
    [ Google | Google Scholar ]
  32. ZEVALLOS, Mauricio Estimation of ARFIMA models: a minimum distance approach. 2019.
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  33. GARCIA, N. L. Global labor market developments. 2019.
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  34. GARCIA, N. L. Hidden Markov random field models applied to color homogeneity evaluation in dyed textiles images. 2019.
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  35. GARCIA, N. L. Mestres e Doutores do Século XXI. 2019.
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  36. MAIA, R. P. A discrete competing risks mixed model with masked causes: a cow longevity study. 2019.
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  37. DIAS, R. https://impa.br/eventos-do-impa/eventos-2019/32o-coloquio-brasileiro-de-matematica/. 2019.
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  38. KIIHL, S. F. Bioinformática e Estatística. 2019.
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  39. V. A. González-López Stochastic Profile of Strains of Zika from Tropical and Subtropical Regions. 2019.
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  40. V. A. González-López Partition Markov Model for Multiple Processes. 2019.
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  41. V. A. González-López Statistical Inference in Copula Models and Markov Processes IV (in ICNAAM 2019). 2019.
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  42. V. A. González-López Sample Selection Procedure in Daily Trading Volume Processes. 2019.
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  43. V. A. González-López Partition Markov model for multiple processes. 2019.
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  44. V. A. González-López Stochastic Profile of Strains of Zika from Tropical and Subtropical Regions. 2019.
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2018

  1. CARVALHO, B. S. Big data e dados de pesquisa em saúde. 2018.
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  2. CARVALHO, B. S. Métodos estatísticos para detecção de mutações e para identificação de genes associados a fenótipos de interesse. 2018.
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  3. CARVALHO, B. S. Avanços na tecnologia de informação e impacto no diagóstico e terapêutica do câncer: o exemplo do big data. 2018.
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  4. CARVALHO, B. S. Gestão de dados na Unicamp. 2018.
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  5. AZEVEDO, C. L. N. Binary regression models: inference and applications. 2018.
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  6. AZEVEDO, C. L. N. Time series and multilevel modeling for longitudinal item response theory data. 2018.
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  7. AZEVEDO, C. L. N. Time series and multilevel modeling for longitudinal item response theory data. 2018.
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  8. AZEVEDO, C. L. N. . 2018.
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  9. GALLESCO, C. Tempos locais suaves para cadeias de Markov e aplicações. 2018.
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  10. BERNARDINI, D. F. On uniform closeness of local times of Markov chains and i.i.d. sequences. 2018.
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  11. Lebensztayn, E. Resultados assintóticos para um modelo estocástico de difusão de rumor em grafos finitos. 2018.
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  12. vilca-Labra, F. E. A Robust multivariate Birnbaum-Saunders regression models. 2018.
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  13. vilca-Labra, F. E. A robust multivariate Birnbaum-Saunders distribution: EM-estimation. 2018.
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  14. vilca-Labra, F. E. A robust multivariate Birnbaum-Saunders distribution: EM-estimation. 2018.
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  15. vilca-Labra, F. E. Deletion measures for Linear Mixed Models using Skew-Normal/Independent Distributions. 2018.
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  16. vilca-Labra, F. E. Linear Mixed Models using Skew-Normal/Independent Distributions: Diagnostic analysis. 2018.
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  17. PINHEIRO, H. P. Discrete survival models to evaluate performance of students. 2018.
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  18. PINHEIRO, H. P. A bivariate discrete survival mixed model to evaluate performance of students in Calculus I and Linear Algebra. 2018.
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  19. GARCIA, J. E. Foreign exchange dependence through different copula models. 2018.
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  20. GARCIA, J. E. Independence Test for Continuous or Discrete Random Variables. 2018.
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  21. GARCIA, J. E. Optimal Model for a Set of Markov Processes. 2018.
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  22. MATOS, L. A. Estimation and diagnostics in multivariate models for censored data. 2018.
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  23. HOTTA, L. K. On the robustness of the principal volatility components. 2018.
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  24. Rodrigues-Motta, M. Identification of early respondents based on EEG signals. 2018.
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  25. Rodrigues-Motta, M. Identifying Potential Biomarkers Through Bivariate MALDI-MS Data. 2018.
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  26. ZEVALLOS, Mauricio Covariance Prediction in Large Portfolio Allocation. 2018.
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  27. ZEVALLOS, Mauricio Estimation of ARFIMA models: A minimum distance approach. 2018.
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  28. ZEVALLOS, Mauricio Séries Temporais, Econometria e Finanças. 2018.
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  29. GARCIA, N. L. Identification of early respondents based on EEG signals. 2018.
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  30. GARCIA, N. L. Modeling textile images with hidden Gibbs random fields. 2018.
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  31. GARCIA, N. L. Interacting cluster point process model for epidermal nerve fibers. 2018.
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  32. MAIA, R. P. ?INDICADORES DE DESEMPENHO DOS ALUNOS REINCIDENTES NAS DISCIPLINAS DE EXATAS DO CURSO SEMIPRESENCIAL DE LICENCIATURA EM CIÊNCIAS. 2018.
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  33. MAIA, R. P. A BIVARIATE DISCRETE SURVIVAL MIXED MODEL TO EVALUATE PERFORMANCE OF STUDENTS IN CALCULUS I AND LINEAR ALGEBRA. 2018.
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  34. DIAS, R. Deformastion, Non Euclidean metrics towards Spatio-Temporal Process. 2018.
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  35. KIIHL, S. F. MLML2R: An R Package for Maximum Likelihood Estimation of DNA Methylation and Hydroxymethylation Proportions. 2018.
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  36. KIIHL, S. F. MLML2R: EFFICIENT SIMULTANEOUS MAXIMUM LIKELIHOOD ESTIMATION OF DNA METHYLATION AND HYDROXYMETHYLATION PROPORTIONS. 2018.
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  37. Benaglia, T. Visuospatial Reasoning Trajectories and Death in a Study of the Oldest Old: A Formal Evaluation of Their Association. 2018.
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  38. V. A. González-López Bayesian Sensitivity Analysis for Asymmetric Copulas with Cubic Sections. 2018.
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  39. V. A. González-López Similarity between Strains of Zika from Tropical and Subtropical Regions. 2018.
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  40. V. A. González-López Statistical Inference in Copula Models and Markov Processes III (in ICNAAM 2018). 2018.
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2017

  1. PINHEIRO, A. O High Dimensional Classification Part II. 2017.
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  2. PINHEIRO, A. Hadamard Differentiability and Asymptotics for a CSI Functional. 2017.
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  3. PINHEIRO, A. Some Results on Wavelet Analysis of Functional Data. 2017.
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  4. PINHEIRO, A. O High Dimensional Classification Part I. 2017.
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  5. PINHEIRO, A. Wavelet regression and generalized linear models with continuous distributions. 2017.
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  6. PINHEIRO, A. Wavelet statistical analysis in multitemporal SAR and satellite images. 2017.
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  7. CARVALHO, B. S. Brazilian Initiative on Precision Medicine: Statistical Perspectives. 2017.
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  8. AZEVEDO, C. L. N. Time Series and Multilevel Modeling for Longitudinal Item Response Theory Data. 2017.
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  9. AZEVEDO, C. L. N. A general Cholesky decomposition based modeling of longitudinal IRT data. 2017.
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  10. AZEVEDO, C. L. N. Teoria da Resposta ao Item e avaliações educacionais. 2017.
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  11. AZEVEDO, C. L. N. . 2017.
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  12. PINHEIRO, H. P. Modelling the performance of engineering major students.. 2017.
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  13. PINHEIRO, H. P. Multinomial and Discrete survival models to evaluate performance of students. 2017.
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  14. GARCIA, J. E. Inspecting Discrepancies between Industrial Processes. 2017.
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  15. GARCIA, J. E. Comparison of Stochastic Processes. 2017.
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  16. MATOS, L. A. Heavy-Tailed Longitudinal Linear Mixed Models for Multiple Censored Responses Data. 2017.
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  17. MATOS, L. A. Heavy-tailed longitudinal regression models for censored data: A likelihood based perspective. 2017.
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  18. HOTTA, L. K. Equity Premium Prediction by Sparse Pooling of Parsimonious State-Dependent Models. 2017.
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  19. HOTTA, L. K. Forecast combination with state-dependent models: equity premium prediction. 2017.
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  20. HOTTA, L. K. Robust bootstrap densities for dynamic conditional correlation. 2017.
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  21. HOTTA, L. K. Robust bootstrap forecast densities for GARCH and DCC returns and volatilities. 2017.
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  22. Rodrigues-Motta, M. Analysis of spectrometry data using a discretization of a bivariate-beta distribution. 2017.
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  23. Rodrigues-Motta, M. Added value from Classic to Bayesian approach. 2017.
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  24. ZEVALLOS, Mauricio Integrated variance estimation using realised measures under microstructure, jumps and outliers. 2017.
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  25. GARCIA, N. L. Bayesian wavelet shrinkage with beta priors for curve estimation with lognormal positive errors. 2017.
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  26. MAIA, R. P. Modelos não-lineares mistos aplicados ao ajuste de curvas de produção de ovos de aves poedeiras.. 2017.
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  27. MAIA, R. P. Modelos não lineares mistos aplicados ao ajuste de curvas de produção de ovos. 2017.
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  28. DIAS, R. A bit of splines, deformation, diffeomorphism, non-euclidean metrics toward spatial temporal processes. 2017.
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  29. V. A. González-López Stochastic Distance between Burkitt lymphoma/leukemia Strains. 2017.
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  30. V. A. González-López Statistical Inference in Copula Models and Markov Processes II (in ICNAAM 2017). 2017.
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  31. V. A. González-López Consistent Estimation of Partition Markov Models. 2017.
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  32. V. A. González-López Further Investigations: a Needed Tool. 2017.
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2016

  1. PINHEIRO, A. Wavelet statistical analysis in multitemporal SAR images. 2016.
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  2. PINHEIRO, A. Wavelet regressio ad generalized linear models. 2016.
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  3. PINHEIRO, A. Wavelet Statistical Analysis of Multitemporal SAR and satellite images. 2016.
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  4. AZEVEDO, C. L. N. Multilevel Item Response Theory Models. 2016.
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  5. AZEVEDO, C. L. N. Modelo de Teoria de Resposta ao Item unidimensional assimétrico de grupos múltiplos: aplicação aos dados do Sistema de Avaliação da Educação Básica (SAEB), de 2011. 2016.
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  6. AZEVEDO, C. L. N. Modelos da Teoria de Resposta ao Item assimétricos de grupos múltiplos para respostas politômicas nominais e ordinais sob um enfoque bayesiano. 2016.
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  7. GALLESCO, C. Comparação uniforme dos tempos locais de cadeias de Markov e sequências i.i.d.. 2016.
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  8. PINHEIRO, H. P. Modelling the proportion of failed courses and GPA scores for engineering major. 2016.
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  9. GARCIA, J. E. Consistent proximity between N-grams. 2016.
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  10. GARCIA, J. E. Dissimilarity between Markovian Processes applied to Industrial Processes. 2016.
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  11. Rodrigues-Motta, M. Positive Responses Augmented by Zeros in Experiments with Incomplete Block Design. 2016.
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  12. Rodrigues-Motta, M. A Mixed-Effect Model for Positive Responses Augmented by Zeros. 2016.
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  13. ZEVALLOS, Mauricio Minimum Distance Estimation of Stochastic Conditional Duration Models. 2016.
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  14. GARCIA, N. L. Analysis of Aggregated Functional Data from Mixed Populations with Application to Energy Consumption. 2016.
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  15. GARCIA, N. L. Cluster processes with repulsion: a model for epidermic nerve fibers. 2016.
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  16. GARCIA, N. L. Como escrever "matematiquês". 2016.
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  17. MAIA, R. P. A Discrete Mixed Competing Risk Model for Discrete Time with Masked Causes. 2016.
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  18. MAIA, R. P. Variance Component Estimation on Discrete-time Competing Risks analysis with Masked Causes. 2016.
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  19. MAIA, R. P. Discrete time competing risks analysis with mas- ked causes. 2016.
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  20. Benaglia, T. A Generalized Non-Parametric Genotype Caller using an EM-like Algorithm. 2016.
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  21. Benaglia, T. A generalized non-parametric genotype caller using an EM-like Algorithm. 2016.
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  22. V. A. González-López Full Interaction Partition Estimation in Stochastic Processes. 2016.
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  23. V. A. González-López Statistical Inference in Copula Models and Markov Processes. 2016.
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  24. Lachos, V. H. Likelihood-based Inference for Mixed-Effects Models with Censored Response Using the Multivariate-t Distribution. 2016.
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  25. Lachos, V. H. Heavy-tailed longitudinal regression models for censored data: A likelihood based perspective. 2016.
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2015

  1. PINHEIRO, A. . 2015.
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  2. PINHEIRO, A. Wavelet Analysis of SAR Data. 2015.
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  3. PINHEIRO, A. Self-modeling ordinal regression with time invariant covariates. 2015.
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  4. PINHEIRO, A. Self-Modeling Ordinal Model with Time Invariant Covariates --- An Application to Prostate Cancer Data. 2015.
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  5. PINHEIRO, A. Wavelet statistical of satellite images. 2015.
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  6. AZEVEDO, C. L. N. Modelos da Teoria de Resposta ao Item Multidimensionais Assimétricos de Grupos Múltiplos Para Respostas Dicotômicas sob um Enfoque Bayesiano. 2015.
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  7. AZEVEDO, C. L. N. Longitudinal multiple-group IRT modelling: covariance pattern selection using MCMC and RJMCMC. 2015.
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  8. GALLESCO, C. Dynamic uniqueness for chains of infinite order. 2015.
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  9. GALLESCO, C. Dynamic uniqueness and phase transition for chains of infinite order. 2015.
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  10. PINHEIRO, H. P. Analysis of academic performance of students via quasi U-statistics and generalized linear mixed models. 2015.
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  11. PINHEIRO, H. P. Constrained hypotheses testing via quasi U-statistics and its application to undergraduate performance assessment. 2015.
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  12. PINHEIRO, H. P. Comparison of groups of longitudinal sequences by quasi U-statistics. 2015.
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  13. GARCIA, J. E. Independence tests based on the size of longest increasing subsequence. 2015.
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  14. GARCIA, J. E. Optimal partition of Markov models and automatic classification of languages. 2015.
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  15. HOTTA, L. K. Modelo Geoestatístico com Processos de Poisson Não Homogêneo. 2015.
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  16. HOTTA, L. K. MGARCH models: Tradeoff between feasibility and dynamic dependencies in volatilities and covariances. 2015.
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  17. HOTTA, L. K. Quasi-likelihood estimation of GARCH models with missing values. 2015.
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  18. HOTTA, L. K. Minicurso: Modelos da la Família GARCH Univaruados y Multivariados. 2015.
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  19. Rodrigues-Motta, M. A Mixed-Effect Model for Positive Responses Augmented by Zeros. 2015.
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  20. Rodrigues-Motta, M. . 2015.
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  21. ZEVALLOS, Mauricio Minimum Distance Estimation of Stochastic Conditional Duration Models. 2015.
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  22. ZEVALLOS, Mauricio Estimation of the Autococorrelation Function of Long-Memory Processes. 2015.
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  23. ZEVALLOS, Mauricio Assessing Stock Market Dependence and Contagion. 2015.
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  24. ZEVALLOS, Mauricio . 2015.
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  25. ZEVALLOS, Mauricio Forecasting intraday VaR of an equity portfolio. 2015.
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  26. GARCIA, N. L. What is perfect simulation and what can it do perfectly for you. 2015.
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  27. GARCIA, N. L. Rumor processes on N and discrete renewal processes. 2015.
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  28. GARCIA, N. L. Análise de dados funcionais em Quimiometria. 2015.
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  29. V. A. González-López 3rd Symposium on Highlights in Copula Modeling. 2015.
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  30. V. A. González-López Theory and Applications of Copulas. 2015.
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  31. V. A. González-López Estimation in Partition Markov Models. 2015.
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  32. V. A. González-López Markov Partition Models for Epstein Barr Virus. 2015.
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  33. Lachos, V. H. Minicurso-Misturas Finitas de distribuições assimétricas. 2015.
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  34. Lachos, V. H. Augmented mixed beta regression models for periodontal proportion data. 2015.
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2014

  1. PINHEIRO, A. Wavelet Functional Analysis of Variance for Dependent Errors. 2014.
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  2. PINHEIRO, A. Wavelet Functional Analysis for Dependent Errors. 2014.
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  3. PINHEIRO, A. Classification of Time Series Under Contamination. 2014.
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  4. PINHEIRO, A. Agrupamento e Classificação de Séries Temporais. 2014.
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  5. AZEVEDO, C. L. N. . 2014.
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  6. AZEVEDO, C. L. N. Bayesian inference for Birnbaum-Saunders mixed models for censored responses e Bayesian Inference in beta and inflated beta regression models. 2014.
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  7. AZEVEDO, C. L. N. Multidimensional Item Response Theory models with multivariate skew normal latent trait distributions under the centered parameterization: bayesian parameter estimation, structural selection and model fit assessment. 2014.
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  8. AZEVEDO, C. L. N. Bayesian longitudinal item response modeling with restricted covariance pattern structures. 2014.
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  9. AZEVEDO, C. L. N. Introdução à Teoria da Resposta ao Item: Conceitos, aplicações e temas de pesquisa. 2014.
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  10. GALLESCO, C. Constrained Information Transmission on Erdos-Renyi graphs. 2014.
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  11. GALLESCO, C. Constrained Information Transmission on Erdos-Renyi graphs. 2014.
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  12. GALLESCO, C. Information Transmission on Erdos-Renyi graphs. 2014.
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  13. PINHEIRO, H. P. Comparison of groups of longitudinal sequences by quasi U-statistics. 2014.
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  14. PINHEIRO, H. P. Modelling performance of students with bivariate generalized linear mixed models. 2014.
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  15. PINHEIRO, H. P. Análise de Desempenho Acadêmico de estudantes da Unicamp. 2014.
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  16. GARCIA, J. E. Interaction partition. Structure of interacting coordinates for a multivariate stochastic process. 2014.
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  17. Rodrigues-Motta, M. A Mixed-Effect Model for Positive Responses Augmented by Zeros. 2014.
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  18. ZEVALLOS, Mauricio Minimum Distance Estimation of High Frequency Transaction Data. 2014.
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  19. ZEVALLOS, Mauricio Minimum Distance Estimation of Stochastic Conditional Duration Models. 2014.
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  20. ZEVALLOS, Mauricio Minimum Distance Estimation of Stochastic Conditional Duration Models. 2014.
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  21. ZEVALLOS, Mauricio Estimación del Riesgo Bursátil Peruano: cuánto influyen los metales y el mercado internacional?. 2014.
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  22. GARCIA, N. L. Bayesian analysis for spectroscopy data. 2014.
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  23. GARCIA, N. L. Rumor processes viewed as renewal processes. 2014.
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  24. GARCIA, N. L. Functional Data in Chemometrics. 2014.
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  25. GARCIA, N. L. Rumor processes viewed as discrete renewal processes. 2014.
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  26. GARCIA, N. L. Mesa Redondo sobre a Pós Graduação em Estatística no Brasil. 2014.
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  27. GARCIA, N. L. Statistical analysis of NIR spectroscopy data. 2014.
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  28. GARCIA, N. L. Functional Data Analysis applied to chemometrics. 2014.
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  29. DIAS, R. Analysis of Aggregated Functional Data from Mixed Populations with Application to Energy Consumption. 2014.
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  30. DIAS, R. Modeling Aggregate Funcional Data. 2014.
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  31. KIIHL, S. F. Statistical methods for preprocessing, integration, and quality assessment of synthetic lethality data. 2014.
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  32. KIIHL, S. F. Comparison of groups of longitudinal sequences by quasi U-statistics. 2014.
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  33. KIIHL, S. F. Statistical methods for preprocessing, integration, and quality assessment of synthetic lethality data. 2014.
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  34. KIIHL, S. F. PREPROCESSING AND QUALITY ASSESSMENT OF MICROARRAY-BASED SYNTHETIC LETHALITY DATA. 2014.
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  35. Benaglia, T. Effectiveness and Cost-Effectiveness of Cytosponge Screening for Barrett's Esophagus. 2014.
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  36. Benaglia, T. Effectiveness and Cost-Effectiveness of Cytosponge Screening for Barrett's Esophagus. 2014.
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  37. V. A. González-López Detecting regime changes in Markov models. 2014.
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  38. V. A. González-López Confidence Bands in Kendall Plots. 2014.
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  39. V. A. González-López A estatística é pop. 2014.
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  40. V. A. González-López Minimal Markov Models. 2014.
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  41. V. A. González-López An independence test based on random permutations. 2014.
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  42. Lachos, V. H. Modelos de Regresión para Datos Censurados con Aplicaciones en R. 2014.
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  43. Lachos, V. H. Bayesian Analysis of censored linear regression models with scale mixtures of normal distribution. 2014.
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  44. Lachos, V. H. Likelihood Based Inference Mixed-Effects Models with Censored Responses Using the Multivariate-t Distribution. 2014.
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  45. Lachos, V. H. New developments in non-Gaussian mixture modeling. 2014.
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2013

  1. PINHEIRO, A. Wavelet Functional Analysis Via Quasi U-Statistics. 2013.
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  2. PINHEIRO, A. Quasi U-statistics: Reasoning and Asymptotics. 2013.
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  3. AZEVEDO, C. L. N. Bayesian Inference in Birnbaum-Saunders Nonlinear Regression Models Based on Scale-Mixture of Normals. 2013.
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  4. AZEVEDO, C. L. N. A New Testlet Model. 2013.
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  5. AZEVEDO, C. L. N. On the using of distances to measure goodness of fit in Item Response Theory models: a Bayesian perspective. 2013.
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  6. AZEVEDO, C. L. N. Teoria da Resposta ao Item: Conceitos e aplicações (mini-curso). 2013.
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  7. AZEVEDO, C. L. N. Uma introdução à Teoria da Resposta ao Item. 2013.
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  8. GALLESCO, C. Large deviations for the cover time of two-dimensional torus. 2013.
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  9. GALLESCO, C. Localization for a random walk in a slowly decreasing random potential. 2013.
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  10. GALLESCO, C. Introducão aos passeios aleatórios em meios aleatórios. 2013.
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  11. GALLESCO, C. Large deviations for the cover time of two-dimensional torus. 2013.
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  12. PINHEIRO, H. P. Árvores de Regressão para Dados Censurados Correlacionados. 2013.
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  13. GARCIA, J. E. Model correction for bivariate Bernoulli Markov procecesses based on copula theory. 2013.
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  14. GARCIA, J. E. ESTIMATING THE STRUCTURE OF INTERACTING COORDINATES FOR A MULTIVARIATE STOCHASTIC PROCESS. 2013.
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  15. HOTTA, L. K. Efeito dos outliers na estimação dos modelos de volatilidade estocástica. 2013.
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  16. HOTTA, L. K. Estimation and testing of hypotheses in the heteroskedastic canonical model of contagion using instrumental variables. 2013.
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  17. HOTTA, L. K. Bootstrap prediction in DCC-GARCH multivariate volatility model with normal distribution. 2013.
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  18. HOTTA, L. K. Generalization of the Mixture Model Using a Copula Function. 2013.
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  19. ZEVALLOS, Mauricio Estimation of long-memory times series with missing data. 2013.
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  20. ZEVALLOS, Mauricio Práctica Estadística: Visualización de datos, modelos y sentido común. 2013.
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  21. ZEVALLOS, Mauricio Estimación de Volatilidad utilizando datos de alta frecuencia. 2013.
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  22. ZEVALLOS, Mauricio Volatilidad realizada en el mercado bursátil peruano. 2013.
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  23. GARCIA, N. L. A Hierarchical model for aggregated functional data: A Bayesian Approach. 2013.
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  24. GARCIA, N. L. Functional data analysis of Near-infrared (NIR) spectroscopy data. 2013.
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  25. DIAS, R. A Hierarchical Model for Aggregated Functional Data. 2013.
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  31. V. A. González-López Detecting Regime Changes In Markov Models. 2013.
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  32. V. A. González-López A Bayesian approach for convex combination of two Gumbel-Barnett copulas. 2013.
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  35. Lachos, V. H. Bayesian Inference in Censored Mixed-Effects Models Using Heavy-Tailed Distributions. 2013.
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  36. Lachos, V. H. Bayesian Inference in Mixed Effects Models for Censored Data with Applications to HIV Studies. 2013.
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  37. Lachos, V. H. Nonlinear mixed-effects models and diagnostics for censored HIV viral loads with CD4 measurement error. 2013.
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2012

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  28. V. A. González-López Markovian Model Selection for Contaminated Stochastic Processes. 2012.
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  29. V. A. González-López A Bayesian Test for the Intraclass Correlation Coefficient. 2012.
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  30. V. A. González-López Robust model selection for stochastic processes. 2012.
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  31. V. A. González-López An independence test based on random permutations. 2012.
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  33. Lachos, V. H. Linear Mixed Models and their extensions. 2012.
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2011

  1. PINHEIRO, A. Quasi U-Statistics for Functiobnal Data Analysis. 2011.
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2010

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  36. V. A. González-López A Bayesian Test for the Intraclass Correlation Coefficient. 2010.
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2009

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  20. ZEVALLOS, Mauricio Minimum Distance Estimation of Long-range Dependent Porcesses. 2009.
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  23. ZEVALLOS, Mauricio Dependencia y contagio en mercados financieros. 2009.
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  24. ZEVALLOS, Mauricio Quantile Estimation for Dependent Data: Aplications to Finance. 2009.
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  31. V. A. González-López Secondary stress, intensity and F0 in Brazilian Portuguese. 2009.
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  32. V. A. González-López A nonparemetric independence test. 2009.
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2008

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  26. Lachos, V. H. Inferência e diagnóstico em modelos para dados de contagem com excesso de zeros. 2008.
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  29. Lachos, V. H. Likelihood Based Inference for Skew-Normal Independent Linear Mixed Models. 2008.
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Arquivo gerado a partir dos currículos Lattes dos pesquisadores. Data do processamento: 02/06/2025 09:35:38
Os resultados estão sujeitos a falhas devido a eventuais inconsistências no preenchimento dos currículos Lattes pelos pesquisadores. Caso note algum problema, por favor, contacte o responsável por esta página: informatica@ime.unicamp.br.