Title: Copula-Based Estimation and Statistical Process Control for
Author: Takeshi Emura, Weiru Chen and Ting-Hsuan Long
Description: Estimation and statistical process control are performed under
Available are statistical methods in Long and Emura (2014 JCSA),

Author: Takeshi Emura, Weiru Chen, Ting-Hsuan Long, Xinwei Huang

Author: Takeshi Emura,  Xinwei Huang, Weiru Chen, Ting-Hsuan Long
Huang and Emura(2019, in revision) and Huang, Chen and Emura (2019-, in revision).

Huang and Emura (2019 Commun Stat-Simul) <DOI:10.1080/03610918.2019.1602647> and Huang, Chen and Emura (2019-, in revision).

Author: Takeshi Emura, Xinwei Huang, Weiru Chen, Ting-Hsuan Long

Author: Takeshi Emura, Xinwei Huang, Weiru Chen, Ting-Hsuan Long, Li-Hsien Sun
Sun et al. (2020 to appear in JSS Series in Statistics, Springer), and Huang, Chen and Emura (2019-, in revision).

Author: Takeshi Emura, Xinwei Huang, Ting-Hsuan Long, Li-Hsien Sun
and Huang and Emura (2021, in revision).

Title: Copula Markov Model with Dependent Censoring
Description: Perform likelihood estimation and corresponding analysis under the copula-based Markov chain model for serially dependent event times with a dependent terminal event. A two stage estimation method is applied for estimating model parameters. Two copula functions are used for measuring dependence. One is used for modeling serial dependence in recurrent event times. The other one is for modeling dependent censoring. The baseline hazard functions are modeled by the Weibull distributions. See Huang (2019) <https://etd.lib.nctu.edu.tw/cgi-bin/gs32/ncugsweb.cgi?o=dncucdr&s=id=%22GC106225601%22.&searchmode=basic> for detail.

Description: Perform likelihood estimation and corresponding analysis under the copula-based Markov chain model for serially dependent event times with a dependent terminal event. Available are statistical methods in Huang, Wang and Emura (2020, JJSD accepted).

Title: Association Analysis of Bivariate Survival Data Based on Copulas
Description: Perform association analysis of bivariate survival data based on copula models.
Two different ways to estimate the association parameter in copula models are implemented.
A goodness-of-fit test for a given copula model is implemented.
See Emura, Lin and Wang (2010) <doi.org/10.1016/j.csda.2010.03.013> for details.