王 婉倫

研究成果

每年研究成果 2008 2011 2013 2015 2017 2018 2019 2020 2021 2022 2023 2024 2025

• 54 Article

每年研究成果

每年研究成果

搜尋結果

• 2025

  Multivariate contaminated normal linear mixed models applied to Alzheimer’s disease study with censored and missing data

  Lin, T. I. & Wang, W. L., 2025 3月, 於: Statistical Methods in Medical Research. 34, 3, p. 490-507 18 p.

  研究成果: Article › 同行評審
  1 引文 斯高帕斯（Scopus）
• 2024

  Bayesian multivariate nonlinear mixed models for censored longitudinal trajectories with non-monotone missing values

  Wang, W. L., Castro, L. M. & Lin, T. I., 2024 7月, 於: Metrika. 87, 5, p. 585-605 21 p.

  研究成果: Article › 同行評審

  • Nonlinear Mixed Model 100%
  • Missing Values 89%
  • Mixed Model 79%
  • Trajectory 57%
  • Longitudinal Data 49%
  1 引文 斯高帕斯（Scopus）

• Mixtures of t factor analysers with censored responses and external covariates: An application to educational data from Peru

  Wang, W. L., Castro, L. M., Li, H. J. & Lin, T. I., 2024 5月, 於: British Journal of Mathematical and Statistical Psychology. 77, 2, p. 316-336 21 p.

  研究成果: Article › 同行評審

  • Education 86%
  • Peru 81%
  • Cluster Analysis 70%
  • Equipment and Supplies 47%
  • Limit of Detection 41%
  2 引文 斯高帕斯（Scopus）

• On moments of truncated multivariate normal/independent distributions

  Lin, T. I. & Wang, W. L., 2024 1月, 於: Journal of Multivariate Analysis. 199, 105248.

  研究成果: Article › 同行評審

  • Moment 62%
  • Double Exponential Distribution 27%
  • Repository 25%
  • Non-normality 22%
  • Heavy-tailed Distribution 22%

• Robust Bayesian inference for the censored mixture of experts model using heavy-tailed distributions

  Mirfarah, E., Naderi, M., Lin, T. I. & Wang, W. L., 2024, (Accepted/In press) 於: Advances in Data Analysis and Classification.

  研究成果: Article › 同行評審

• Three-way data clustering based on the mean-mixture of matrix-variate normal distributions

  Naderi, M., Tamandi, M., Mirfarah, E., Wang, W. L. & Lin, T. I., 2024 11月, 於: Computational Statistics and Data Analysis. 199, 108016.

  研究成果: Article › 同行評審
  1 引文 斯高帕斯（Scopus）
• 2023

  Flexible modeling of multiple nonlinear longitudinal trajectories with censored and non-ignorable missing outcomes

  Lin, T. I. & Wang, W. L., 2023 3月, 於: Statistical Methods in Medical Research. 32, 3, p. 593-608 16 p.

  研究成果: Article › 同行評審

  • Nonlinear Mixed Effects Model 100%
  • Limit of Detection 76%
  • CD4 Lymphocyte Count 73%
  • Datasets 56%
  • Trajectory 56%
  7 引文 斯高帕斯（Scopus）

• Model-based clustering via mixtures of unrestricted skew normal factor analyzers with complete and incomplete data

  Wang, W. L. & Lin, T. I., 2023 9月, 於: Statistical Methods and Applications. 32, 3, p. 787-817 31 p.

  研究成果: Article › 同行評審

  • Model-based Clustering 100%
  • Incomplete Data 95%
  • Clustering 61%
  • Skew 61%
  • Missing Values 47%

• Multivariate Contaminated Normal Censored Regression Model: Properties and Maximum Likelihood Inference

  Wang, W. L., 2023, 於: Journal of Computational and Graphical Statistics. 32, 4, p. 1671-1684 14 p.

  研究成果: Article › 同行評審

  • Censored Regression Model 100%
  • Censored Regression 86%
  • Likelihood Inference 77%
  • Maximum Likelihood 63%
  • Inference 51%
  2 引文 斯高帕斯（Scopus）

• Robust mixture regression modeling based on the normal mean-variance mixture distributions

  Naderi, M., Mirfarah, E., Wang, W. L. & Lin, T. I., 2023 4月, 於: Computational Statistics and Data Analysis. 180, 107661.

  研究成果: Article › 同行評審

  • Mixture Distribution 100%
  • Mixture Model 82%
  • Regression Model 64%
  • Regression 59%
  • Modeling 50%
  6 引文 斯高帕斯（Scopus）
• 2022

  A robust factor analysis model based on the canonical fundamental skew-t distribution

  Lin, T. I., Chen, I. A. & Wang, W. L., 2022, (Accepted/In press) 於: Statistical Papers. 64, 2, p. 367-393 27 p.

  研究成果: Article › 同行評審

  • Factor Analysis 100%
  • t-distribution 92%
  • Skew 72%
  • Model-based 71%
  • Skewness 57%

• Extending finite mixtures of nonlinear mixed-effects models with covariate-dependent mixing weights

  Wang, W. L., Yang, Y. C. & Lin, T. I., 2022, (Accepted/In press) 於: Advances in Data Analysis and Classification. 18, 2, p. 271-307 37 p.

  研究成果: Article › 同行評審

  • Nonlinear Mixed Effects Model 100%
  • Finite Mixture 88%
  • Empirical Bayes Estimation 50%
  • Dependent 47%
  • Simulation Experiment 39%

• Multivariate linear mixed models with censored and nonignorable missing outcomes, with application to AIDS studies

  Lin, T. I. & Wang, W. L., 2022, (Accepted/In press) 於: Biometrical Journal. 64, 7, p. 1325-1339 15 p.

  研究成果: Article › 同行評審

  • Linear Mixed Model 100%
  • Mixed Model 99%
  • Longitudinal Data 61%
  • Non-response 55%
  • Conditional Expectation 51%
  11 引文 斯高帕斯（Scopus）

• Multivariate measurement error models with normal mean-variance mixture distributions

  Mirfarah, E., Naderi, M., Lin, T. I. & Wang, W. L., 2022 12月, 於: Stat. 11, 1, e503.

  研究成果: Article › 同行評審

  • Measurement Error 100%
  • Mixture Distribution 93%
  • Measurement Error Model 83%
  • Mean-variance 65%
  • Blood Pressure 22%
  1 引文 斯高帕斯（Scopus）

• Robust clustering of multiply censored data via mixtures of t factor analyzers

  Wang, W. L. & Lin, T. I., 2022 3月, 於: Test. 31, 1, p. 22-53 32 p.

  研究成果: Article › 同行評審

  • Censored Data 100%
  • Clustering 64%
  • Maximum Likelihood Estimation 62%
  • Multiplication 55%
  • Estimator 54%
  5 引文 斯高帕斯（Scopus）
• 2021

  Mixtures of factor analyzers with covariates for modeling multiply censored dependent variables

  Wang, W. L., Castro, L. M., Hsieh, W. C. & Lin, T. I., 2021 10月, 於: Statistical Papers. 62, 5, p. 2119-2145 27 p.

  研究成果: Article › 同行評審

  • Censored Data 100%
  • Covariates 68%
  • Multiplication 55%
  • Dependent 45%
  • Modeling 44%
  7 引文 斯高帕斯（Scopus）

• Multivariate t semiparametric mixed-effects model for longitudinal data with multiple characteristics

  Taavoni, M., Arashi, M., Wang, W. L. & Lin, T. I., 2021, 於: Journal of Statistical Computation and Simulation. 91, 2, p. 260-281 22 p.

  研究成果: Article › 同行評審

  • Longitudinal Data 100%
  • Mixed Effects Model 82%
  • Semiparametric Model 54%
  • Mixed Model 54%
  • Multivariate T-distribution 22%
  8 引文 斯高帕斯（Scopus）

• On moments of folded and truncated multivariate Student-t distributions based on recurrence relations

  Galarza, C. E., Lin, T. I., Wang, W. L. & Lachos, V. H., 2021 8月, 於: Metrika. 84, 6, p. 825-850 26 p.

  研究成果: Article › 同行評審

  • Student-t Distribution 100%
  • t-distribution 84%
  • Recurrence relation 71%
  • Moment 49%
  • Repository 25%
  15 引文 斯高帕斯（Scopus）

• Robust clustering via mixtures of t factor analyzers with incomplete data

  Wang, W. & Lin, T., 2021 7月 5, 於: Advances in Data Analysis and Classification.

  研究成果: Article › 同行評審
  7 引文 斯高帕斯（Scopus）
• 2020

  Automated learning of mixtures of factor analysis models with missing information

  Wang, W. L. & Lin, T. I., 2020 12月, 於: Test. 29, 4, p. 1098-1124 27 p.

  研究成果: Article › 同行評審

  • Missing Information 100%
  • Factor Analysis 86%
  • Missing Values 64%
  • Learning 62%
  • Factor Models 57%
  4 引文 斯高帕斯（Scopus）

• Bayesian analysis of multivariate linear mixed models with censored and intermittent missing responses

  Wang, W. L., 2020 8月 30, 於: Statistics in Medicine. 39, 19, p. 2518-2535 18 p.

  研究成果: Article › 同行評審

  • Markov Chains 100%
  • Linear Mixed Model 90%
  • Limit of Detection 76%
  • Bayesian Analysis 75%
  • Uncertainty 66%
  9 引文 斯高帕斯（Scopus）

• Extending finite mixtures of t linear mixed-effects models with concomitant covariates

  Yang, Y. C., Lin, T. I., Castro, L. M. & Wang, W. L., 2020 8月, 於: Computational Statistics and Data Analysis. 148, 106961.

  研究成果: Article › 同行評審

  • Linear Mixed Effects Model 100%
  • Finite Mixture 91%
  • Model-based Clustering 36%
  • Students 32%
  • Model Reduction 29%
  6 引文 斯高帕斯（Scopus）

• Finite mixtures of multivariate scale-shape mixtures of skew-normal distributions

  Wang, W. L., Jamalizadeh, A. & Lin, T. I., 2020 12月 1, 於: Statistical Papers. 61, 6, p. 2643-2670 28 p.

  研究成果: Article › 同行評審

  • Finite Mixture 100%
  • Skew-normal Distribution 91%
  • Normal Distribution 76%
  • Flexibility 44%
  • Maximum Likelihood Estimation 43%
  10 引文 斯高帕斯（Scopus）

• Multivariate-t linear mixed models with censored responses, intermittent missing values and heavy tails

  Lin, T. I. & Wang, W. L., 2020 5月 1, 於: Statistical Methods in Medical Research. 29, 5, p. 1288-1304 17 p.

  研究成果: Article › 同行評審

  • Linear Mixed Model 100%
  • Heavy Tails 94%
  • Missing Values 94%
  • Linear Models 62%
  • Multivariate Data 58%
  29 引文 斯高帕斯（Scopus）
• 2019

  Bayesian semiparametric modeling for HIV longitudinal data with censoring and skewness

  Castro, L. M., Wang, W. L., Lachos, V. H., Inácio de Carvalho, V. & Bayes, C. L., 2019 5月 1, 於: Statistical Methods in Medical Research. 28, 5, p. 1457-1476 20 p.

  研究成果: Article › 同行評審

  • Normal Distribution 100%
  • Skewness 90%
  • Longitudinal Data 89%
  • Censoring 85%
  • Skew-normal Distribution 72%
  11 引文 斯高帕斯（Scopus）

• Mixture of multivariate t nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values

  Wang, W. L., 2019 3月 12, 於: Test. 28, 1, p. 196-222 27 p.

  研究成果: Article › 同行評審

  • Nonlinear Mixed Model 100%
  • Longitudinal Data 98%
  • Missing Values 89%
  • Mixed Model 79%
  • Nonlinear Mixed Effects Model 58%
  7 引文 斯高帕斯（Scopus）

• Mixtures of restricted skew-t factor analyzers with common factor loadings

  Wang, W. L., Castro, L. M., Chang, Y. T. & Lin, T. I., 2019 6月 1, 於: Advances in Data Analysis and Classification. 13, 2, p. 445-480 36 p.

  研究成果: Article › 同行評審

  • Common factor 100%
  • Skew 69%
  • Factor Models 36%
  • Leptokurtic 14%
  • Model-based Clustering 14%
  4 引文 斯高帕斯（Scopus）

• Model-based clustering of censored data via mixtures of factor analyzers

  Wang, W. L., Castro, L. M., Lachos, V. H. & Lin, T. I., 2019 12月, 於: Computational Statistics and Data Analysis. 140, p. 104-121 18 p.

  研究成果: Article › 同行評審

  • Model-based Clustering 100%
  • Censored Data 70%
  • Censoring 68%
  • Cluster Validation 40%
  • Censored Observations 29%
  19 引文 斯高帕斯（Scopus）
• 2018

  Bayesian inference on multivariate-t nonlinear mixed-effects models for multiple longitudinal data with missing values

  Wang, W. L. & Castro, L. M., 2018, 於: Statistics and its Interface. 11, 2, p. 251-264 14 p.

  研究成果: Article › 同行評審

  • Nonlinear Mixed Effects Model 100%
  • Missing Values 85%
  • Longitudinal Data 76%
  • Predictive Inference 35%
  • Markov Chain Monte Carlo Methods 26%
  4 引文 斯高帕斯（Scopus）

• Extending multivariate-t linear mixed models for multiple longitudinal data with censored responses and heavy tails

  Wang, W. L., Lin, T. I. & Lachos, V. H., 2018 1月 1, 於: Statistical Methods in Medical Research. 27, 1, p. 48-64 17 p.

  研究成果: Article › 同行評審

  • Linear Mixed Model 100%
  • Heavy Tails 94%
  • Longitudinal Data 84%
  • Linear Models 62%
  • HIV 54%
  41 引文 斯高帕斯（Scopus）

• Multivariate longitudinal data analysis with censored and intermittent missing responses

  Lin, T. I., Lachos, V. H. & Wang, W. L., 2018 8月 30, 於: Statistics in Medicine. 37, 19, p. 2822-2835 14 p.

  研究成果: Article › 同行評審

  • Multivariate Data Analysis 100%
  • Longitudinal Data Analysis 96%
  • Linear Mixed Model 85%
  • Linear Models 53%
  • Data Analysis 51%
  30 引文 斯高帕斯（Scopus）

• Robust mixtures of factor analysis models using the restricted multivariate skew-t distribution

  Lin, T. I., Wang, W. L., McLachlan, G. J. & Lee, S. X., 2018 2月 1, 於: Statistical Modelling. 18, 1, p. 50-72 23 p.

  研究成果: Article › 同行評審

  • Factor Analysis 100%
  • t-distribution 92%
  • Skew 72%
  • Missing Values 63%
  • Model-based Clustering 39%
  23 引文 斯高帕斯（Scopus）
• 2017

  Automated learning of t factor analysis models with complete and incomplete data

  Wang, W. L., Castro, L. M. & Lin, T. I., 2017 9月, 於: Journal of Multivariate Analysis. 161, p. 157-171 15 p.

  研究成果: Article › 同行評審

  開啟存取

  • Incomplete Data 100%
  • Factor Analysis 88%
  • Learning 64%
  • Two-stage Procedure 36%
  • Parameter Estimation 32%
  6 引文 斯高帕斯（Scopus）

• Flexible clustering via extended mixtures of common t-factor analyzers

  Wang, W. L. & Lin, T. I., 2017 7月 1, 於: AStA Advances in Statistical Analysis. 101, 3, p. 227-252 26 p.

  研究成果: Article › 同行評審

  • Clustering 100%
  • Covariance Matrix 77%
  • Covariance matrix 63%
  • Mixture Model 61%
  • Model-based Clustering 52%
  4 引文 斯高帕斯（Scopus）

• Mixture of multivariate t linear mixed models for multi-outcome longitudinal data with heterogeneity

  Wang, W. L., 2017 4月, 於: Statistica Sinica. 27, 2, p. 733-760 28 p.

  研究成果: Article › 同行評審

  • Longitudinal Data 100%
  • Linear Mixed Effects Model 87%
  • Linear Mixed Model 80%
  • Mixed Model 80%
  • Finite Mixture 79%
  10 引文 斯高帕斯（Scopus）

• Multivariate-t nonlinear mixed models with application to censored multi-outcome AIDS studies

  Lin, T. I. & Wang, W. L., 2017 10月 1, 於: Biostatistics. 18, 4, p. 666-681 16 p.

  研究成果: Article › 同行評審

  • Nonlinear Mixed Model 100%
  • Nonlinear Dynamics 82%
  • Mixed Model 79%
  • Nonlinear Mixed Effects Model 58%
  • HIV 43%
  21 引文 斯高帕斯（Scopus）

• Robust skew-t factor analysis models for handling missing data

  Wang, W. L., Liu, M. & Lin, T. I., 2017 11月 1, 於: Statistical Methods and Applications. 26, 4, p. 649-672 24 p.

  研究成果: Article › 同行評審

  • Missing Data 100%
  • Factor Analysis 97%
  • Maximum Likelihood Estimation 94%
  • Missing Values 72%
  • Skew 70%
  10 引文 斯高帕斯（Scopus）
• 2016

  Maximum likelihood inference for the multivariate t mixture model

  Wang, W. L. & Lin, T. I., 2016 7月 1, 於: Journal of Multivariate Analysis. 149, p. 54-64 11 p.

  研究成果: Article › 同行評審

  開啟存取

  • Mixture Model 100%
  • Hessian matrix 70%
  • Likelihood Inference 70%
  • Maximum Likelihood 57%
  • Matrix 50%
  14 引文 斯高帕斯（Scopus）
• 2015

  Approximate methods for maximum likelihood estimation of multivariate nonlinear mixed-effects models

  Wang, W. L., 2015, 於: Entropy. 17, 8, p. 5353-5381 29 p.

  研究成果: Article › 同行評審

  開啟存取

  • Nonlinear Mixed Effects Model 100%
  • Maximum likelihood estimation 82%
  • Maximum Likelihood Estimation 66%
  • Likelihood Function 35%
  • Monte Carlo EM Algorithm 27%
  7 引文 斯高帕斯（Scopus）

• Bayesian analysis of multivariate t linear mixed models with missing responses at random

  Wang, W. L. & Lin, T. I., 2015 11月 22, 於: Journal of Statistical Computation and Simulation. 85, 17, p. 3594-3612 19 p.

  研究成果: Article › 同行評審

  • Bayesian Analysis 100%
  • Multiple Imputation 82%
  • Linear Mixed Model 81%
  • Mixed Model 81%
  • Bayes' Formula 42%
  17 引文 斯高帕斯（Scopus）

• Mixtures of common t-factor analyzers for modeling high-dimensional data with missing values

  Wang, W. L., 2015 3月, 於: Computational Statistics and Data Analysis. 83, p. 223-235 13 p.

  研究成果: Article › 同行評審

  • Missing Values 100%
  • High-dimensional Data 96%
  • Modeling 54%
  • Data Classification 41%
  • Missing at Random 34%
  11 引文 斯高帕斯（Scopus）

• Robust model-based clustering via mixtures of skew-t distributions with missing information

  Wang, W. L. & Lin, T. I., 2015 12月 1, 於: Advances in Data Analysis and Classification. 9, 4, p. 423-445 23 p.

  研究成果: Article › 同行評審

  • Model-based Clustering 100%
  • Missing Values 80%
  • t-distribution 78%
  • Missing Data 69%
  • Skew 61%
  12 引文 斯高帕斯（Scopus）
• 2014

  Multivariate t nonlinear mixed-effects models for multi-outcome longitudinal data with missing values

  Wang, W. L. & Lin, T. I., 2014 7月 30, 於: Statistics in Medicine. 33, 17, p. 3029-3046 18 p.

  研究成果: Article › 同行評審

  • Likelihood Functions 100%
  • Nonlinear Mixed Effects Model 90%
  • Chile 79%
  • Missing Values 77%
  • Fertilization 70%
  29 引文 斯高帕斯（Scopus）
• 2013

  An efficient ECM algorithm for maximum likelihood estimation in mixtures of t-factor analyzers

  Wang, W. L. & Lin, T. I., 2013 4月, 於: Computational Statistics. 28, 2, p. 751-769 19 p.

  研究成果: Article › 同行評審

  • Maximum Likelihood Estimation 100%
  • Conditional Expectation 70%
  • EM Algorithm 51%
  • Convergence Speed 27%
  • Missing Information 26%
  22 引文 斯高帕斯（Scopus）

• Mixtures of common factor analyzers for high-dimensional data with missing information

  Wang, W. L., 2013 5月, 於: Journal of Multivariate Analysis. 117, p. 120-133 14 p.

  研究成果: Article › 同行評審

  開啟存取

  • Missing Information 100%
  • Common Factors 93%
  • Common factor 90%
  • High-dimensional Data 79%
  • Specification 24%
  14 引文 斯高帕斯（Scopus）

• Multivariate skew-normal at linear mixed models for multi-outcome longitudinal data

  Lin, T. I. & Wang, W. L., 2013 6月, 於: Statistical Modelling. 13, 3, p. 199-221 23 p.

  研究成果: Article › 同行評審

  • Longitudinal Data 100%
  • Linear Mixed Model 80%
  • Mixed Model 80%
  • Random Effects 65%
  • Skew 58%
  28 引文 斯高帕斯（Scopus）

• Multivariate t linear mixed models for irregularly observed multiple repeated measures with missing outcomes

  Wang, W. L., 2013 7月, 於: Biometrical Journal. 55, 4, p. 554-571 18 p.

  研究成果: Article › 同行評審

  • Repeated Measures 100%
  • Linear Mixed Model 96%
  • Mixed Model 96%
  • Imputation 60%
  • Longitudinal Data 59%
  32 引文 斯高帕斯（Scopus）
• 2012

  Bayesian analysis of multivariate t linear mixed models using a combination of IBF and Gibbs samplers

  Wang, W. L. & Fan, T. H., 2012 2月, 於: Journal of Multivariate Analysis. 105, 1, p. 300-310 11 p.

  研究成果: Article › 同行評審

  開啟存取

  • Bayesian Analysis 100%
  • Gibbs Sampler 97%
  • Bayes' Formula 84%
  • Linear Mixed Model 81%
  • Mixed Model 81%
  25 引文 斯高帕斯（Scopus）

• Some results on the truncated multivariate t distribution

  Ho, H. J., Lin, T. I., Chen, H. Y. & Wang, W. L., 2012 1月, 於: Journal of Statistical Planning and Inference. 142, 1, p. 25-40 16 p.

  研究成果: Article › 同行評審

  • Multivariate T-distribution 100%
  • Sampling 49%
  • Left Truncation 24%
  • Conditional Density 21%
  • Auxiliary Variables 19%
  53 引文 斯高帕斯（Scopus）
• 2011

  Accelerated life tests for weibull series systems with masked data

  Fan, T. H. & Wang, W. L., 2011 9月, 於: IEEE Transactions on Reliability. 60, 3, p. 557-569 13 p., 5753980.

  研究成果: Article › 同行評審

  • Time-to-failure 100%
  • Maximum likelihood estimation 94%
  • Costs 31%
  41 引文 斯高帕斯（Scopus）