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2020 – today
- 2024
[j20]Wan-Lun Wang
, Yu-Chen Yang, Tsung-I Lin:
Extending finite mixtures of nonlinear mixed-effects models with covariate-dependent mixing weights. Adv. Data Anal. Classif. 18(2): 271-307 (2024)- [j19]Mehrdad Naderi, Mostafa Tamandi, Elham Mirfarah, Wan-Lun Wang, Tsung-I Lin:
Three-way data clustering based on the mean-mixture of matrix-variate normal distributions. Comput. Stat. Data Anal. 199: 108016 (2024) - [j18]Tsung-I Lin, Wan-Lun Wang:
On moments of truncated multivariate normal/independent distributions. J. Multivar. Anal. 199: 105248 (2024) - 2023
- [j17]Mehrdad Naderi, Elham Mirfarah, Wan-Lun Wang, Tsung-I Lin:
Robust mixture regression modeling based on the normal mean-variance mixture distributions. Comput. Stat. Data Anal. 180: 107661 (2023) - [j16]Wan-Lun Wang:
Multivariate Contaminated Normal Censored Regression Model: Properties and Maximum Likelihood Inference. J. Comput. Graph. Stat. 32(4): 1671-1684 (2023) - 2022
- [j15]Wan-Lun Wang, Tsung-I Lin:
Robust clustering via mixtures of t factor analyzers with incomplete data. Adv. Data Anal. Classif. 16(3): 659-690 (2022) - 2020
- [j14]Yu-Chen Yang, Tsung-I Lin, Luis Mauricio Castro, Wan-Lun Wang:
Extending finite mixtures of t linear mixed-effects models with concomitant covariates. Comput. Stat. Data Anal. 148: 106961 (2020)
2010 – 2019
- 2019
- [j13]Wan-Lun Wang, Luis Mauricio Castro, Yen-Ting Chang, Tsung-I Lin:
Mixtures of restricted skew-t factor analyzers with common factor loadings. Adv. Data Anal. Classif. 13(2): 445-480 (2019) - [j12]Wan-Lun Wang, Luis Mauricio Castro, Victor H. Lachos, Tsung-I Lin:
Model-based clustering of censored data via mixtures of factor analyzers. Comput. Stat. Data Anal. 140: 104-121 (2019) - 2017
- [j11]Wan-Lun Wang, Luis Mauricio Castro, Tsung-I Lin:
Automated learning of t factor analysis models with complete and incomplete data. J. Multivar. Anal. 161: 157-171 (2017) - [j10]Wan-Lun Wang, Min Liu, Tsung-I Lin:
Robust skew-t factor analysis models for handling missing data. Stat. Methods Appl. 26(4): 649-672 (2017) - 2016
- [j9]Wan-Lun Wang, Tsung-I Lin:
Maximum likelihood inference for the multivariate t mixture model. J. Multivar. Anal. 149: 54-64 (2016) - 2015
- [j8]Wan-Lun Wang, Tsung-I Lin:
Robust model-based clustering via mixtures of skew-t distributions with missing information. Adv. Data Anal. Classif. 9(4): 423-445 (2015) - [j7]Wan-Lun Wang:
Mixtures of common t-factor analyzers for modeling high-dimensional data with missing values. Comput. Stat. Data Anal. 83: 223-235 (2015) - [j6]Wan-Lun Wang:
Approximate Methods for Maximum Likelihood Estimation of Multivariate Nonlinear Mixed-Effects Models. Entropy 17(8): 5353-5381 (2015) - 2013
- [j5]Wan-Lun Wang, Tsung-I Lin:
An efficient ECM algorithm for maximum likelihood estimation in mixtures of t-factor analyzers. Comput. Stat. 28(2): 751-769 (2013) - [j4]Wan-Lun Wang:
Mixtures of common factor analyzers for high-dimensional data with missing information. J. Multivar. Anal. 117: 120-133 (2013) - 2012
- [j3]Wan-Lun Wang, Tsai-Hung Fan:
Bayesian analysis of multivariate t linear mixed models using a combination of IBF and Gibbs samplers. J. Multivar. Anal. 105(1): 300-310 (2012) - 2011
- [j2]Tsai-Hung Fan, Wan-Lun Wang:
Accelerated Life Tests for Weibull Series Systems With Masked Data. IEEE Trans. Reliab. 60(3): 557-569 (2011) - 2010
- [j1]Wan-Lun Wang, Tsai-Hung Fan:
ECM-based maximum likelihood inference for multivariate linear mixed models with autoregressive errors. Comput. Stat. Data Anal. 54(5): 1328-1341 (2010)
Coauthor Index
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