Refereed Journal Articles (*CA)           

Google Scholar Citations

A-91 Mirfarah E, Naderi M, Lin TI, and Wang WL* (2024) Robust Bayesian inference for the censored mixture of experts model using heavy-tailed distributions Advances in Data Analysis and Classification    https://doi.org/10.1007/s11634-024-00609-2 (SCI) full-text

A-90 Mahdavi A, Desmond AF, Jamalizadeh A and Lin TI* (2024) Skew multiple scaled mixtures of normal distributions with flexible tail behavior and their application to clustering. Journal of Classification (SCI) https://doi.org/10.1007/s00357-024-09470-6  full-text

A-89 Kuoi FY and Lin TI* (2024) Artificial Intelligence methods for the prediction of network intrusion attacks. Journal of Taiwan Intelligent Technologies and Applied Statistics 22(1), 1-25 (In Chinese, 中文撰寫)  full-text  (Invited)

A-88 Naderi M, Tamandi M, Mirfarah E, Wang WL and  Lin TI* (2024) Three-way data clustering based on the mean-mixture of matrix-variate normal distributions Computational Statistics and Data Analysis  199, 108016 (SCI)  full-text

A-87 Wang WL Castro, LM, Huei-Jyun Li and Lin TI* (2024) Mixtures of t factor analyzers with censored responses and external covariates: an application to educational data from Peru. British Journal of Mathematical and Statistical Psychology  77(2), 316–336. (SCI/SSCI)  full-text

A-86 Lin, TI and Wang, WL*  (2024) On moments of truncated multivariate normal/independent distributions.  Journal of Multivariate Analysis 199, 105248  (SCI)  full-text

A-85 Wang WL Castro, LM, and Lin TI* (2024) Bayesian multivariate nonlinear mixed models for censored longitudinal trajectories with non-monotone missing values. Metrika  87(5), 585-605 (SCI) full-text

A-84 Wang, WL, Yang, YC and Lin TI* (2024) Extending finite mixtures of nonlinear mixed-effects models with covariate-dependent mixing weightsAdvances in Data Analysis and Classification 18(2), 271-307 (SCI) full-text

A-83 Lin TI and Wang, WL* (2023) Flexible modeling of multiple nonlinear longitudinal trajectories with censored and non-ignorable missing outcomes. Statistical Methods in Medical Research  32(3), 593–608 (SCI)  full-text

A-82 Wang, WL and Lin TI* (2023) Model-based clustering via mixtures of unrestricted skew normal factor analyzers with complete and incomplete data. Statistical Methods and Applications 32(3), 787–817 (SCI) full-text

A-81 Lin TI, Chen IA and Wang, WL*  (2023) A robust factor analysis model based on the canonical fundamental skew-t distribution. Statistical Papers 64(2), 367–393 (SCI)  full-text

A-80 Naderi M, Mirfarah E, Wang WL and  Lin TI* (2023) Robust mixture regression modeling based on the normal mean-variance mixture distributions Computational Statistics and Data Analysis 180, 107661 (SCI) full-text

A-79 Mirfarah E, Naderi M, Lin TI, and Wang WL* (2022) Multivariate measurement error models with normal mean-variance mixture distributions STAT  11: e503 (SCI) full-text

A-78 Lin TI and Wang, WL*  (2022) Multivariate linear mixed models with censored and nonignorable missing outcomes, with application to AIDS studiesBiometrical Journal  64, 1325–1339 (SCI)  full-text

A-77 Ingrassia S and Lin TI* (2022) The 2nd Special issue on Mixture Models. Econometrics and Statistics 22, 1-2  (Editorial) (SCI) full-text

A-76 Wang, WL and Lin TI* (2022) Robust clustering via mixtures of t factor analyzers with incomplete  dataAdvances in Data Analysis and Classification 16(3) 659-690 (SCI) full-text

A-75 Wang, WL and Lin TI* (2022) Robust clustering of multiply censored data via mixtures of t factor analyzers. TEST 31(1), 22-53 (SCI) full-text

A-74 Galarza CE, Lin, TI, Wang WL and Lachos VH* (2021) On moments of folded and truncated multivariate Student-t distributions based on recurrence relations. Metrika 84(6), 825-850 (SCI) full-text

A-73 Mahdavi A,Amirzadeh V, Jamalizadeh A and Lin TI* (2021) A multivariate flexible skew-symmetric-normal distribution: scale-shape mixtures and parameter estimation via selection representation. Symmetry 13, 1343 (SCI) full-text

A-72 Mahdavi A,Amirzadeh V, Jamalizadeh A and Lin TI* (2021) Maximum likelihood estimation for scale-shape mixtures of flexible generalized skew normal distributions via selection representationComputational Statistics 36(3), 2201-2230 (SCI) full-text

A-71 Lee, SX, Lin, TI and McLachlan GJ* (2021) Mixtures of factor analyzers with fundamental skew symmetric distributions. Advances in Data Analysis and Classification  15(2), 481-512 (SCI) full-text

A-70 Taavoni, M, Arashi, M*, Wang, WL and Lin TI (2021) Multivariate t semiparametric mixed-effects model for longitudinal data with multiple characteristicsJournal of Statistical Computation and Simulation  91(2) 260-281  (SCI) full-text

A-69 Wang, WL, Castro, LM, Hsieh, WC and Lin TI* (2021) Mixtures of factor analyzers with covariates for modeling multiply  censored dependent variables. Statistical Papers 62(5), 2119-2145 (SCI)  full-text

A-68 Naderi, M, Jamalizadeha, A, Wang, WL and Lin TI*  (2020) Evaluating risk measures using the normal mean-variance Birnbaum-Saunders distribution. Springer series- Computational and Methodological Statistics and Biostatistics - Contemporary Essays in Advancement, pp. 187-209 (Book Chapter) full-text (invited)

A-67 Garay AM, Medina, FL*, Cabral CRB and Lin, TI (2020) Bayesian analysis of the p-order integer valued AR process with   zero-inflated Poisson innovationsJournal of Statistical Computation and Simulation 90(11) 1943-1964 (SCI) full-text

A-66 Yang YC, Lin, TI, Castro, LM and Wang, WL* (2020) Extending finite mixtures of t linear mixed-effects models with concomitant covariatesComputational Statistics and Data Analysis  148, 106961, 1-20 (SCI) full-text

A-65 Wang, WL and Lin TI* (2020) Automated learning of mixtures of factor analysis models with missing information. TEST 29(4), 1098-1124 (SCI) full-text

A-64 Hashemia, F, Naderi, M, Jamalizadeha, A and Lin, TI* (2020) A skew factor analysis model based on the normal mean-variance mixture of Birnbaum-Saunders distribution. Journal of Applied Statistics 47(16), 3007-3029  (SCI)  full-text

A-63 Wang, WL, Jamalizadeh, A and Lin TI* (2020) Finite mixtures of multivariate scale-shape mixtures of skew-normal distributions. Statistical Papers 61(6), 2643-2670 (SCI)  full-text  supplemetary materials

A-62 Lin, TI and Wang, WL* (2020) Multivariate-t linear mixed models with censored responses, intermittent missing values and heavy tails. Statistical Methods in Medical Research 29(5), 1288-1304 (SCI) full-text  supplemetary materials

A-61Wang, WL, Castro, LM, Lachos, VH and  Lin, TI* (2019) Model-based clustering of censored data via mixtures of factor analyzers. Computational Statistics and Data Analysis 140, 104-121  (SCI)  full-text

A-60 Naderia M, Hung WL*, Lin, TI and Jamalizadeh A (2019) A novel mixture model using the multivariate normal mean-variance mixture of Birnbaum-Saunders distributions and its application to extrasolar planets  Journal of Multivariate Analysis 171, 126-138  (SCI)  full-text  supplemetary materials

A-59 Tamandi M, Jamalizadeh A and Lin TI* (2019) Shape mixtures of skew-t-normal distributions: characterizations and estimation. Computational Statistics 34(1), 323-347 (SCI)  full-text  supplemetary materials

A-58 Matos LA, Lachos VH*, Lin, TI and Castro LM (2019) Heavy-tailed longitudinal regression models for censored data: A robust parametric approachTEST 28(3), 844-878 (SCI)  full-text

A-57 Wang, WL, Castro, LM, Chang, YT and  Lin, TI* (2019) Mixtures of restricted skew-t factor analyzers with common factor loadings. Advances in Data Analysis and Classification 13(2), 445-480 (SCI) full-text

A-56 Lin, TI, Lachos, VH and Wang, WL* (2018) Multivariate longitudinal data analysis with censored and intermittent missing responses. Statistics in Medicine  37, 2822-2835  (SCI) full-text  supplemetary materials

A-55 Wang, WL*,  Lin, TI and Lachos, VH (2018) Extending multivariate-t linear mixed models for multiple longitudinal data with censored responses and heavy tails. Statistical Methods in Medical Research 27, 48-64 (SCI) full-text  supplemetary materials

A-54  Lin, TI*, Wang, WL, McLachlan GJ and  Lee, SX (2018) Robust mixtures of factor analysis models using the restricted multivariate skew-t distribution Statistical Modelling  28, 50-72 (SCI)  full-text  archive  Example data and code

A-53 Roozegar R, Jamalizadeh A*, Amiri M and Lin TI(2018) On the exact distribution of order statistics arising from a doubly truncated bivariate elliptical distributionMETRON 76, 99-114 (SCI) full-text

A-52 Lin, TI and  Wang, WL* (2017) Multivariate-t nonlinear mixed models with application to censored multi-outcome AIDS studies. Biostatistics 18, 666-681 (SCI) full-text  supplemetary materials

A-51 Wang, WL, Castro, LM and  Lin, TI* (2017) Automated learning of t factor analysis models with complete and incomplete data  Journal of Multivariate Analysis 161, 157-171 (SCI)  full-text  supplemetary materials

A-50 Wang, WL, Min Liu and  Lin, TI* (2017) Robust skew-t factor analysis models for handling missing data. Statistical Methods and Applications  26, 649-672 (SCI)  full-text

A-49 Naderia M, Arabpour, A, Lin, TI* and JamalizadehA* (2017) Nonlinear regression models based on the normal mean-variance mixture of Birnbaum-Saunders distribution. Journal of the Korean Statistical Society 46, 476-485  (SCI)  full-text

A-48 Wang, WL and  Lin, TI* (2017) Flexible clustering via extended mixtures of common t-factor analyzers. Advances in Statistical Analysis 101, 227-252 (SCI)  full-text

A-47 JamalizadehA and  Lin, TI* (2017) A general class of scale-shape mixtures of skew-normal distributions: properties and estimation. Computational Statistics 32, 451-474 (SCI)  full-text

A-46 Wang, WL* and  Lin, TI (2016) Maximum likelihood inference for the multivariate t mixture model. Journal of Multivariate Analysis 149, 54-64 (SCI)  full-text  supplemetary materials

A-45 Garay, AW*, Lachos, VH. and Lin, TI (2016) Nonlinear censored regression models with scale mixtures of normal distributions. Statistics and its Interface 9, 281-293 (SCI)  full-text

A-44 Lin, TI*, McLachlan GJ and  Lee, SX (2016) Extending mixtures of factor models using the restricted multivariate skew-normal distribution. Journal of Multivariate Analysis 143, 398-413 (SCI)  full-text

A-43 Wang, WL and  Lin, TI* (2015) Robust model-based clustering via mixtures of skew-t distributions with missing information. Advances in Data Analysis and Classification 9, 423-445 (SCI)  full-text

A-42 Lin, TI*, Wu, PH, McLachlan GJ and  Lee, SX (2015) A robust factor analysis model using the restricted skew-t distribution. TEST  24, 510-531 (SCI)  full-text

A-41 Liu, M and Lin, TI* (2015) Skew-normal factor analysis models with incomplete data. Journal of Applied Statistics 42, 789-805  (SCI)  full-text

A-40 Wang, WL* and  Lin, TI (2015) Bayesian analysis of multivariate t linear mixed models with missing responses at random. Journal of Statistical Computation and Simulation 85, 3594-3612 (SCI)  full-text

A-39 Wang, WL* and  Lin, TI (2014) Multivariate t nonlinear mixed-effects models for multi-outcome longitudinal data with missing values. Statistics in Medicine 33, 3029-3046 (SCI) full-text

A-38 Lin, TI*, Ho, HJ and Lee CR (2014) Flexible mixture modelling using the multivariate skew-t-normal distribution.  Statistics and Computing 24, 531-546 (SCI)  full-text

A-37 Lin, TI*, McNicholas, PD and Ho, HJ (2014) Capturing patterns via parsimonious mixture models. Statistics and Probability Letters 88, 80-87 (SCI)  full-text  supplemetary materials

A-36 Liu, M* and Lin, TI (2014) A skew-normal mixture regression model.  Educational and Psychological Measurement 74, 139-162 (SSCI)  full-text

A-35 Lin, TI* (2014) Learning from incomplete data via parameterized t mixture models through eigenvalue decomposition. Computational Statistics and Data Analysis 71, 183-195 (SCI)  full-text

A-34 Lin, TI and Wang, WL* (2013) Multivariate skew-normal linear mixed models for multi-outcome longitudinal data.  Statistical Modelling 13, 199-221 (SCI)  full-text

A-33 Wang, WL and  Lin, TI* (2013) An efficient ECM algorithm for maximum likelihood estimation in mixtures of t-factor analyzers. Computational Statistics 28, 751-769 (SCI)  full-text

A-32 Wang, WY and Lin, TI* (2012) Parsimonious Gaussian clustering models with missing information. Journal of the Chinese Statistical Association  50, 142-172 (In Chinese, 中文撰寫 full-text

A-31 Ho, HJ, Lin, TI(Co-first author) , Chang, HH, Haase, HB, Huang, S and Pyne S* (2012) Parametric modeling of cellular state transitions as measured with flow cytometry different tissues. BMC Bioinformatics 13(Suppl 5):S5 (13 pages) (SCI)  full-text

A-30 Ho, HJ, Pyne, S and Lin, TI* (2012) Maximum likelihood inference for mixtures of skew Student-t-normal distributions through practical EM-type algorithms. Statistics and Computing 22, 287-299 (SCI)  full-text

A-29 Ho, HJ, Lin, TI,  Chen, HY and Wang, WL* (2012) Some results on the truncated multivariate t distribution. Journal of Statistical Planning and Inference  142, 25-40  (SCI) full-text R code

A-28 Chen, PJ, Kuo, YC and  Lin, TI* (2011) Classification Rules for heterogeneous multivariate t populations. Journal of Taiwan Intelligent Technologies and Applied Statistics 9, 31-48 (In Chinese, 中文撰寫)   full-text

A-27 Rossin, E, Lin, TI(Co-first author), Ho, HJ, Mentzer, SJ and Pyne, S* (2011) A framework for analytical characterization of monoclonal antibodies based on reactivity profiles in different tissues. Bioinformatics 27, 2746-2753   Software  suppl (SCI)

A-26 Lin, TI* and Lin, TC (2011) Robust statistical modelling using the multivariate skew t distribution with complete and incomplete data. Statistical Modelling 11, 253-277 (SCI) full-text

A-25 Lin, TI* and Wang, WL (2011) Bayesian inference in joint modelling of location and scale parameters of the t distribution for longitudinal data. Journal of Statistical Planning and Inference 141, 1543-1553 (SCI)  full-text

A-24 Ho, HJ and Lin, TI* (2010) Robust linear mixed models using the skew t distribution with application to schizophrenia data. Biometrical Journal 52, 449-469 (SCI) full-text  Data and Software

A-23 Lin TC and Lin, TI* (2010) Supervised learning of multivariate skew normal mixture models with missing information. Computational Statistics 25, 183-201 (SCI)  full-text

A-22 Lin, TI* (2010) Robust mixture modeling using multivariate skew t distributions. Statistics and Computing  20, 343-356 (SCI)  full-text

A-21 Lin, TI*, Ho, HJ and Chen, CL (2009) Analysis of multivariate skew normal models with incomplete data. Journal of Multivariate Analysis 100, 2337-2351 (SCI)  full-text

A-20 Pyne, S, Hu, X, Wang, K, Rossin, E, Lin, TI, Maier, LM, Baecher-Allan, C, McLachlan, GJ, Tamayo, P, Hafler*, DA, De Jager, PL and Mesirov*, JP (2009) Automated high-dimensional flow cytometric data analysis. Proceedings of the National Academy of Sciences (PNAS) USA  106, 8519-8524  (SCI)  full-text  supplemetary materials  Software

A-19 Lin, TI* and Wang, YJ (2009)  A robust approach to joint modeling of mean and scale covariance for longitudinal data. Journal of Statistical Planning and Inference 139, 3013-3026 (SCI)

A-18 Lin, TI*, Ho, HJ, and Shen, PS (2009) Computationally efficient learning of multivariate t mixture models with missing information. Computational Statistics  24, 375-392 (SCI)  full-text

A-17 Lin, TI* (2009) Maximum likelihood estimation for multivariate skew normal mixture models. Journal of Multivariate Analysis 100, 257-265 (SCI)  full-text

A-16 Lin, TI* (2008)  Longitudinal data analysis using t linear mixed models with autoregressive dependence structures. Journal of Data Scienece (A special issue in memory of Professor Jack C. Lee) 6, 333-355  full-text

A-15 Hsu*, YL, Lin, TI, and Lee, CF (2008) Constant Elasticity of Variance (CEV) Option Pricing Model: Integration and Detailed Derivations. Mathematics and Computers in Simulation 79, 60-71 (SCI)  full-text

A-14 Lin, TI*, and Lee, JC (2008) Estimation and prediction in linear mixed models with skew normal random effects for longitudinal data. Statistics in Medicine  27, 1490-1507 (SCI)  full-text

A-13 Lin, TI*, and Ho, HJ (2008) A simplified approach to inverting the autocovariance matrix of a general ARMA(p,q) process, Statistics & Probability Letters 78, 36-41 full-text code (SCI)

A-12 Lin, TI* and Lee, JC and Hsieh WJ (2007) Robust mixture modeling using the skew t distribution. Statistics and Computing 17, 81-92. (SCI)  full-text

A-11 Lin, TI* and Lee, JC (2007) Bayesian analysis of hierarchical linear mixed modeling using  the multivariate t distribution. Journal of Statistical Planning and Inference 137, 484-495 (SCI)  full-text

A-10 Lin, TI*, Lee, JC and Yen, SY (2007) Finite mixture modelling using the skew normal distribution, Statistica Sinica 17, 909-927. (SCI)  full-text

A-9 Lin, TI* (2006) Bayesian analysis of time series regressions with multivariate t autoregressive errors. Journal of the Chinese Statistical Association  44, 108-129.   full-text

A-8  Lin, TI*, Lee, JC, and Ho, Hj (2006) On fast supervised learning for normal mixture models with missing information. Pattern Recognition 39, 1177-1187. (SCI)  full-text

A-7  Lin, TI* and Lee, JC (2006) A robust approach to t linear mixed models applied to multiple sclerosis data. Statistics in Medicine 25,1397-1412. (SCI)  full-text

A-6 Lee, JC*, Lin, TI, Lee, KJ and Hsu, YL (2005) Bayesian analysis of Box-Cox transformed linear mixed models with ARMA(p,q) dependence. Journal of Statistical Planning and Inference 133, 435-451. (SCI)  full-text

A-5  Hsu, YL*, Kueng, TL, Lee, JC and Lin, TI (2005) Parameter estimation and future value prediction of generalized growth curve model with power transformation, random effects and general AR(g) dependence, Journal of the Chinese Statistical Association 43, 451-471. full-text

A-4. Lee, JC*, Lee, CF, Wang, RS and Lin, TI (2004) Binomial and multinomial option pricing models: review and integration, Advance in Quantitative Finance and Accounting (New Series) 1, 271 - 295.   full-text

A-3  Lee, JC*, Wang, RS and Lin, TI (2004) On the inverse of the autocorrelation matrix for an AR(p) process.  
      Journal of the Chinese Statistical Association 42, 81-89.  full-text

A-2  Lin, TI*, Lee, JC and Ni, HF (2004) Bayesian analysis of mixture modelling using the multivariate t distribution. Statistics and Computing 14, 119-130. (SCI)  full-text

A-1  Lin, TI* and Lee, JC (2003) On modelling data from degradation sample paths over time. Australian and New Zealand Journal of Statistics 45, 257-270. (SCI)  full-text