成功大學統計學系

系所成員
姓名 王婉倫
職稱 教授
專長領域 長期資料分析、多變量分析、統計計算、貝氏統計
E-mail wangwl@gs.ncku.edu.tw
辦公室 管理學院統計系館3樓62310室
聯絡電話 (06)2757575~53632
個人網頁 https://sites.google.com/gs.ncku.edu.tw/wangwl/
經 歷(Main Experiences)
  • 成功大學統計學系 教授       (2022/02 ~ 目前)
  • 逢甲大學統計學系 教授       (2016/08 ~ 2022/01)
  • 逢甲大學統計學系 副教授    (2013/08 ~ 2016/07)
  • 逢甲大學統計學系 助理教授 (2010/08 ~ 2013/07)
學歷(Education)
  • 中央大學統計研究所 博士
  • 中央大學統計研究所 碩士
  • 東海大學統計學系 學士
研究方向(Research Field)
  • 長期資料分析 Longitudinal Data Analysis
  • 高維度資料分析 High-dimensional Data Analysis
  • 統計計算 Statistical Computing
  • 貝氏統計 Bayesian Statistics

1. Wang, W.L. and Lin, T.I.* (2022) Robust clustering of multiply censored data via mixtures of t factor analyzers. TEST, 31, 22-53 https://doi.org/10.1007/s11749-021-00766-y 

2. Wang, W.L. and Lin, T.I.* (2021) Robust clustering via mixtures of t factor analyzers with incomplete data. Advances in Data Analysis and Classification, https://doi.org/10.1007/s11634-021-00453-8 

3.  Galarza, C.E., Lin, T.I., Wang, W.L. and Lachos, V.H.* (2021) On moments of folded and truncated multivariate Student-t distributions based on recurrence relations. Metrika 84, 825–850 https://doi.org/10.1007/s00184-020-00802-1

4.   Taavoni, M., Arashi, M.*, Wang, W.L. and Lin, T.I. (2021) Multivariate t semiparametric mixed-effects model for longitudinal data with multiple characteristics. Journal of Statistical Computation and Simulation, 91(2), 260-281 https://doi.org/10.1080/00949655.2020.1812608.

5.   Wang, W.L., Jamalizadeh, A. and Lin T.I.* (2020) Finite mixtures of multivariate scale-shape mixtures of skew-normal distributions. Statistical Papers, 61, 2643–2670.

6.    Wang, W.L.* (2020) Bayesian analysis of multivariate linear mixed models with censored and intermittent missing responses. Statistics in Medicine, 39(19), 2518–2535.

7.    Wang, W.L., Castro, L.M., Hsieh, W.C. and Lin T.I.* (2020) Mixtures of factor analyzers with covariates for modeling multiply censored dependent variables. Statistical Papers, https://doi.org/10.1007/s00362-020-01177-1.

8.    Yang, Y.C., Lin, T.I., Castro, L.M. and Wang, W.L.* (2020) Extending finite mixtures of linear mixed-effects models with concomitant covariates. Computational Statistics and Data Analysis, 148, 106961. https://doi.org/10.1016/j.csda.2020.106961.

9.      Lin, T.I. and Wang, W.L.* (2020) Multivariate-t linear mixed models with censored responses, intermittent missing values and heavy tails. Statistical Methods in Medical Research, 29(5), 1288–1304.

10.  Wang, W.L. and Lin, T.I.* (2020) Automated learning of mixtures of factor analysis models with missing information. TEST, 29:1098–1124 https://doi.org/10.1007/s11749-020-00702-6

11.  Wang, W.L., Castro, L.M., Lachos, V.H. and Lin, T.I.* (2019) Model-based clustering of censored data via mixtures of factor analyzers. Computational Statistics and Data Analysis, 140, 104–121. 

12.  Wang, W.L., Castro, L.M., Chang, Y.T. and Lin, T.I.* (2019) Mixtures of restricted skew-t factor analyzers with common factor loadings. Advances in Data Analysis and Classification, 13(2), 445–480. 

13.  Castro, L.M.*, Wang, W.L., Lachos, V.H., Carvalho, V.I. and Bayes, C.L. (2019) Bayesian semiparametric modeling for HIV longitudinal data with censoring and skewness. Statistical Methods in Medical Research, 28(5), 1457–1476. 

14.  Wang, W.L.* (2019) Mixture of multivariate t nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values. TEST, 28(1), 196–222. 

15.  Lin, T.I., Lachos, V.H., Wang, W.L.* (2018) Multivariate longitudinal data analysis with censored and intermittent missing responses. Statistics in Medicine, 37(19), 2822–2835. 

16.  Lin, T.I.*, Wang, W.L., McLachlan, G.J. and Lee, S.X. (2018) Robust mixtures of factor analysis models using the restricted multivariate skew-t distribution. Statistical Modelling, 18(1), 50–72. 

17.  Wang, W.L.* and Castro, L.M. (2018) Bayesian inference on multivariate-t nonlinear mixed-effects models for multiple longitudinal data with missing values. Statistics and Its Interface, 11(2), 251–264. 

18.  Wang, W.L.*, Lin, T.I. and Lachos, V.H. (2018) Extending multivariate-t linear mixed models for multiple longitudinal data with censored responses and heavy tails. Statistical Methods in Medical Research, 27(1), 48–64. 

19.  Wang, W.L., Liu, M. and Lin, T.I.* (2017) Robust skew-t factor analysis models for handling missing data. Statistical Methods and Applications, 26(4), 649–672. 

20.  Lin, T.I. and Wang, W.L.* (2017) Multivariate-t nonlinear mixed models with application to censored multi-outcome AIDS studies. Biostatistics, 18(4), 666–681. 

21.  Wang, W.L., Castro, L.M., and Lin, T.I.* (2017) Automated learning of t factor analysis models with complete and incomplete data. Journal of Multivariate Analysis, 161, 157–171.

22.  Wang, W.L.* (2017) Mixture of multivariate-t linear mixed models for multi-outcome longitudinal data with heterogeneity. Statistica Sinica, 27, 733–760.

23.  Wang, W.L. and Lin, T.I.* (2017) Flexible clustering via extended mixtures of common t-factor analyzers. AStA Advances in Statistical Analysis, 101, 227–252. 

24.  Wang, W.L.* and Lin, T.I. (2016) Maximum likelihood inference for the multivariate t mixture model. Journal of Multivariate Analysis, 149, 54-64. 

25.  Wang, W.L. and Lin, T.I.* (2015) Robust model-based clustering via mixtures of skew-t distributions with missing information. Advances in Data Analysis and Classification, 9, 423-445.

26.  Wang, W.L.* (2015) Approximate methods for maximum likelihood estimation of multivariate nonlinear mixed-effects models. Entropy, 17, 5353-5381. 

27.  Wang, W.L.* and Lin, T.I. (2015) Bayesian analysis of multivariate t linear mixed models with missing responses at random. Journal of Statistical Computation and Simulation, 85(17), 3594-3612. 

28.  Wang, W.L.* (2015) Mixtures of common t-factor analyzers for modeling high-dimensional data with missing values. Computational Statistics and Data Analysis, 83, 223-235. 

29.  Wang, W.L.* and Lin, T.I. (2014) Multivariate t nonlinear mixed-effects models for multi-outcome longitudinal data with missing values. Statistics in Medicine, 33(17), 3029-3046. 

30.  Wang, W.L.* (2013) Mixtures of common factor analyzers for high-dimensional data with missing information. Journal of Multivariate Analysis, 117, 120-133.

31.  Wang, W.L. and Lin, T.I.* (2013) An efficient ECM algorithm for maximum likelihood estimation in mixtures of t-factor analyzers. Computational Statistics, 28 (2), 751-769. 

32.  Wang, W.L.* (2013) Multivariate t linear mixed models for irregularly observed multiple repeated measures with missing outcomes. Biometrical Journal, 55 (4), 554-571. 

33.   Lin, T.I. and Wang, W.L.* (2013) Multivariate skew-normal linear mixed models for multi-outcome longitudinal data. Statistical Modelling, 13 (3), 199-221. 

34. Wang, W.L.* and Fan, T.H. (2012) Bayesian analysis of multivariate t linear mixed models using a combination of IBF and Gibbs samplers. Journal of Multivariate Analysis, 105 (1), 300-310. 

1.     Wang, W.L.* (2015) Approximate methods for maximum likelihood estimation of multivariate nonlinear mixed-effects models. Proceedings of the 60th World Statistics Congress – ISI2015, July 26-31, 2015 in Rio de Janeiro, RJ, Brazil.

2.     Lin, T.I.* and Wang, W.L. (2015) Bayesian computational strategies for multivariate t linear mixed models with missing outcomes. Proceedings of the 60th World Statistics Congress – ISI2015, July 26-31, 2015 in Rio de Janeiro, RJ, Brazil.

3.   Wang, W.L.* and Fan, T.H. (2011) Bayesian inference in multivariate t linear mixed models using the IBF-Gibbs sampler. Section on Quality and Productivity – JSM 2011 Proceedings, Aug., Miami, Florida, USA. 523-535.

4.    Wang, W.L.* and Fan, T.H. (2010) Multivariate t linear mixed models with AR(p) errors for multiple longitudinal data. Section on Statistical Computing – JSM 2010 Proceedings, Aug., Vancouver, BC, Canada. 649-663.

5.  Wang, W.L.* and Fan, T.H. (2009) Test and prediction in multivariate linear mixed models for multiple longitudinal data. Section on Statistical Computing – JSM 2009 Proceedings, Aug., Washington, D.C., USA. 546-559.

6.    Fan, T.H.* and Wang, W.L. (2007) Bayesian inference for progressive step-stress life-testing with the Box-Cox transformation. ISI 2007, Aug., Lisbon, Portugal.

1. Naderi, M., Jamalizadeh, A., Wang, W.L. and Lin T.I.* (2020) Evaluating risk measures using the normal mean-variance Birnbaum-Saunders distribution. In: Bekker A., Chen G., Ferreira J. (eds) Computational and Methodological Statistics and Biostatistics. Emerging Topics in Statistics and Biostatistics. Springer, Cham, 187-209. https://doi.org/10.1007/978-3-030-42196-0_8.

2. 王婉倫 (2019, 5) 多元長期追蹤資料分群方法與應用。研究成果報導,自然科學簡訊,自然科學及永續研究發展司-科技部,第三十一卷第二期, 67-71

3. Ho, H.J., Lin, T.I., Wang, W.L., Garay, A.M., Lachos, V.H., and Castro, L.M. (2015) R TTmoment package: sampling and calculating the first and second moments for the doubly truncated multivariate t distribution. R package version 3.2.3, 2015-05-04.

 

 

  • 科技部優秀年輕學者研究計畫 (107/08/01 ~ 110/07/31)
  • 106學年度逢甲大學教學傑出獎教師
  • 99年度魏慶榮統計論文獎優等(第十九屆南區統計研討會)
  • 96年度中國統計學社論文獎-佳作獎
  • 96年、98年斐陶斐榮譽會員 (國立中央大學分會推薦)

 

 

@FCU

指導學生獲110年度中國統計學社論文獎-優等獎 (研究生:劉佩萱)

指導學生獲109年度中國統計學社論文獎-佳作獎 (研究生:李易聰)

指導學生獲第三屆全國碩士生統計研究成果海報競賽特優獎 (研究生:劉俊賢)

指導學生獲107年度中國統計學社論文獎-優等獎 (研究生:楊郁成)

指導學生獲106年度中國統計學社論文獎-佳作獎 (研究生:黃彥菱、黃筠庭)

指導106年度科技部大專生專題研究計畫-由巨量資料分析探討台灣高齡化下的社會參與 (學生:許家欣)

指導105年度科技部大專生專題研究計畫-由巨量資料探討各國觀光產業發展之研究 (學生:陳啟昌)

指導103年度科技部大專生專題研究計畫-混合迴歸模型及其應用研究 (學生:楊雅惠)

指導學生獲102年度中國統計學社論文獎-佳作獎 (研究生:徐偉舜)