depend.truncation: Statistical Inference for Parametric and Semiparametric Models Based on Dependently Truncated Data

Suppose that one can observe bivariate random variables (X, Y) only when X<=Y holds. Data (X_j, Y_j), subject to X_j<=Y_j, for all j=1,...,n, are called truncated data. Parametric approach (Emura & Konno 2012 Stat Papers), semiparametric approach (Chaieb et al. 2006 Biometrika; Emura et al. 2011 Sinica), and the nonparametric maximum likelihood approach (Emura & Wang 2012 JMVA) are implemented for statistical inference on (X, Y), when X and Y are dependent. Also included is truncated data on the number of deaths at each year (1963-1980) for Japanese male centenarians (Emura and Murotani 2015).

Version: 2.2
Depends: mvtnorm
Published: 2015-03-06
Author: Takeshi EMURA
Maintainer: Takeshi EMURA <emura at stat.ncu.edu.tw>
License: GPL-2
NeedsCompilation: no
CRAN checks: depend.truncation results

Downloads:

Reference manual: depend.truncation.pdf
Package source: depend.truncation_2.2.tar.gz
Windows binaries: r-devel: depend.truncation_2.2.zip, r-release: depend.truncation_2.2.zip, r-oldrel: depend.truncation_2.2.zip
OS X Snow Leopard binaries: r-release: depend.truncation_2.2.tgz, r-oldrel: depend.truncation_2.2.tgz
OS X Mavericks binaries: r-release: depend.truncation_2.2.tgz
Old sources: depend.truncation archive