Tsung-I Lin

According to our database, Tsung-I Lin authored at least 37 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

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

Wan-Lun Wang, Yu-Chen Yang, Tsung-I Lin

Adv. Data Anal. Classif., June, 2024

On moments of truncated multivariate normal/independent distributions.

Tsung-I Lin, Wan-Lun Wang

J. Multivar. Anal., 2024

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

Mehrdad Naderi, Mostafa Tamandi, Elham Mirfarah, Wan-Lun Wang, Tsung-I Lin

Comput. Stat. Data Anal., 2024

2023

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

Mehrdad Naderi, Elham Mirfarah, Wan-Lun Wang, Tsung-I Lin

Comput. Stat. Data Anal., April, 2023

2022

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

Wan-Lun Wang, Tsung-I Lin

Adv. Data Anal. Classif., 2022

2021

A Multivariate Flexible Skew-Symmetric-Normal Distribution: Scale-Shape Mixtures and Parameter Estimation via Selection Representation.

Abbas Mahdavi, Vahid Amirzadeh, Ahad Jamalizadeh, Tsung-I Lin

Symmetry, 2021

Maximum likelihood estimation for scale-shape mixtures of flexible generalized skew normal distributions via selection representation.

Abbas Mahdavi, Vahid Amirzadeh, Ahad Jamalizadeh, Tsung-I Lin

Comput. Stat., 2021

Mixtures of factor analyzers with scale mixtures of fundamental skew normal distributions.

Sharon X. Lee, Tsung-I Lin, Geoffrey J. McLachlan

Adv. Data Anal. Classif., 2021

2020

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

Yu-Chen Yang, Tsung-I Lin, Luis Mauricio Castro, Wan-Lun Wang

Comput. Stat. Data Anal., 2020

2019

A novel mixture model using the multivariate normal mean-variance mixture of Birnbaum-Saunders distributions and its application to extrasolar planets.

Mehrdad Naderi, Wen-Liang Hung, Tsung-I Lin, Ahad Jamalizadeh

J. Multivar. Anal., 2019

Shape mixtures of skew-<i>t</i>-normal distributions: characterizations and estimation.

Mostafa Tamandi, Ahad Jamalizadeh, Tsung-I Lin

Comput. Stat., 2019

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

Wan-Lun Wang, Luis Mauricio Castro, Victor H. Lachos, Tsung-I Lin

Comput. Stat. Data Anal., 2019

Editorial for the 4th Special Issue on advances in mixture models.

Jochen Einbeck, John Hinde, Salvatore Ingrassia, Tsung-I Lin, Paul D. McNicholas

Comput. Stat. Data Anal., 2019

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

Wan-Lun Wang, Luis Mauricio Castro, Yen-Ting Chang, Tsung-I Lin

Adv. Data Anal. Classif., 2019

2017

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

Wan-Lun Wang, Min Liu, Tsung-I Lin

Stat. Methods Appl., 2017

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

Wan-Lun Wang, Luis Mauricio Castro, Tsung-I Lin

J. Multivar. Anal., 2017

A general class of scale-shape mixtures of skew-normal distributions: properties and estimation.

Ahad Jamalizadeh, Tsung-I Lin

Comput. Stat., 2017

2016

Maximum likelihood inference for the multivariate t mixture model.

Wan-Lun Wang, Tsung-I Lin

J. Multivar. Anal., 2016

Extending mixtures of factor models using the restricted multivariate skew-normal distribution.

Tsung-I Lin, Geoffrey J. McLachlan, Sharon X. Lee

J. Multivar. Anal., 2016

The Third Special Issue on Advances in Mixture Models.

John Hinde, Salvatore Ingrassia, Tsung-I Lin, Paul D. McNicholas

Comput. Stat. Data Anal., 2016

2015

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

Wan-Lun Wang, Tsung-I Lin

Adv. Data Anal. Classif., 2015

2014

Flexible mixture modelling using the multivariate skew-t-normal distribution.

Tsung-I Lin, Hsiu J. Ho, Chia-Rong Lee

Stat. Comput., 2014

Learning from incomplete data via parameterized t mixture models through eigenvalue decomposition.

Tsung-I Lin

Comput. Stat. Data Anal., 2014

2013

An efficient ECM algorithm for maximum likelihood estimation in mixtures of <i>t</i>-factor analyzers.

Wan-Lun Wang, Tsung-I Lin

Comput. Stat., 2013

2012

Maximum likelihood inference for mixtures of skew Student-t-normal distributions through practical EM-type algorithms.

Hsiu J. Ho, Saumyadipta Pyne, Tsung-I Lin

Stat. Comput., 2012

Parametric modeling of cellular state transitions as measured with flow cytometry.

Hsiu J. Ho, Tsung-I Lin, Hannah H. Chang, Steven B. Haase, Sui Huang, Saumyadipta Pyne

BMC Bioinform., 2012

2011

A framework for analytical characterization of monoclonal antibodies based on reactivity profiles in different tissues.

Elizabeth Rossin, Tsung-I Lin, Hsiu J. Ho, Steven J. Mentzer, Saumyadipta Pyne

Bioinform., 2011

Parametric modeling of cellular state transitions as measured with flow cytometry.

Saumyadipta Pyne, Steven B. Haase, Hsiu J. Ho, Tsung-I Lin

Proceedings of the IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences, 2011

2010

Robust mixture modeling using multivariate skew <i>t</i> distributions.

Tsung-I Lin

Stat. Comput., 2010

Supervised learning of multivariate skew normal mixture models with missing information.

Tzy-Chy Lin, Tsung-I Lin

Comput. Stat., 2010

Automated High-Dimensional Flow Cytometric Data Analysis.

Saumyadipta Pyne, Xinli Hu, Kui Wang, Elizabeth Rossin, Tsung-I Lin, Lisa Maier, Clare Baecher-Allan, Geoffrey J. McLachlan, Pablo Tamayo, David Hafler, Philip L. De Jager, Jill P. Mesirov

Proceedings of the Research in Computational Molecular Biology, 2010

2009

Analysis of multivariate skew normal models with incomplete data.

Tsung-I Lin, Hsiu J. Ho, Chiang L. Chen

J. Multivar. Anal., 2009

Maximum likelihood estimation for multivariate skew normal mixture models.

Tsung-I Lin

J. Multivar. Anal., 2009

Computationally efficient learning of multivariate <i>t</i> mixture models with missing information.

Tsung-I Lin, Hsiu J. Ho, Pao-Sheng Shen

Comput. Stat., 2009

2007

Robust mixture modeling using the skew <i>t</i> distribution.

Tsung-I Lin, Jack C. Lee, Wan J. Hsieh

Stat. Comput., 2007

2006

On fast supervised learning for normal mixture models with missing information.

Tsung-I Lin, Jack C. Lee, Hsiu J. Ho

Pattern Recognit., 2006

2004

Bayesian analysis of mixture modelling using the multivariate t distribution.

Tsung-I Lin, Jack C. Lee, Huey F. Ni

Stat. Comput., 2004