| depend.truncation-package {depend.truncation} | R Documentation |
Statistical Methods for the Analysis of Dependently Truncated Data
Description
Estimation and testing methods for dependently truncated data. Semi-parametric methods are based on Emura et al. (2011), Emura & Wang (2012), and Emura & Murotani (2015). Parametric approaches are based on Emura & Konno (2012) and Emura & Pan (2017). A regression approach is based on Emura & Wang (2016). Quasi-independence tests are based on Emura & Wang (2010). Right-truncated data for Japanese male centenarians are given by Emura & Murotani (2015).
Details
| Package: | depend.truncation |
| Type: | Package |
| Version: | 3.0 |
| Date: | 2018-02-27 |
| License: | GPL-2 |
Author(s)
Takeshi Emura <takeshiemura@gmail.com>
References
Emura T, Wang W (2010), Testing quasi-independence for truncation data. Journal of Multivariate Analysis 101, 223-239.
Emura T, Wang W, Hung HN (2011), Semiparametric Inference for Copula Models for Truncated Data, Stat Sinica 21: 349-367.
Emura T, Konno Y (2012), Multivariate Normal Distribution Approaches for Dependently Truncated Data. Statistical Papers 53 (No.1), 133-149.
Emura T, Wang W (2012), Nonparametric Maximum Likelihood Estimation for Dependent Truncation Data Based on Copulas, Journal of Multivariate Analysis 110: 171-88
Emura T, Murotani K (2015), An Algorithm for Estimating Survival Under a Copula-based Dependent Truncation Model, TEST 24 (No.4): 734-751.
Emura T, Wang W (2016), Semiparametric Inference for an Accelerated Failure Time Model with Dependent Truncation, Ann Inst Stat Math 68 (5): 1073-94.
Emura T, Pan CH (2017), Parametric likelihood inference and goodness-of-fit for dependently left-truncated data, a copula-based approach, Statistical Papers, doi:10.1007/s00362-017-0947-z.