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dblcens  

Compute the NPMLE of Distribution Function from Doubly Censored Data, Plus the Empirical Likelihood Ratio for F(T)
View on CRAN: Click here


Download and install dblcens package within the R console
Install from CRAN:
install.packages("dblcens")

Install from Github:
library("remotes")
install_github("cran/dblcens")

Install by package version:
library("remotes")
install_version("dblcens", "1.1.9")



Attach the package and use:
library("dblcens")
Maintained by
Yifan Yang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2002-03-08
Latest Update: 2023-01-13
Description:
Doubly censored data, as described in Chang and Yang (1987) ), are commonly seen in many fields. We use EM algorithm to compute the non-parametric MLE (NPMLE) of the cummulative probability function/survival function and the two censoring distributions. One can also specify a constraint F(T)=C, it will return the constrained NPMLE and the -2 log empirical likelihood ratio for this constraint. This can be used to test the hypothesis about the constraint and, by inverting the test, find confidence intervals for probability or quantile via empirical likelihood ratio theorem. Influence functions of hat F may also be calculated, but currently, the it may be slow.
How to cite:
Yifan Yang (2002). dblcens: Compute the NPMLE of Distribution Function from Doubly Censored Data, Plus the Empirical Likelihood Ratio for F(T). R package version 1.1.9, https://cran.r-project.org/web/packages/dblcens. Accessed 05 Jun. 2026.
Previous versions and publish date:
1.1.1 (2004-06-30 10:55), 1.1.2 (2005-02-21 09:37), 1.1.3 (2005-08-07 10:52), 1.1.4 (2008-04-04 22:39), 1.1.5 (2010-04-27 21:09), 1.1.6 (2012-10-29 08:58), 1.1.7 (2012-12-17 05:50), 1.1 (2002-03-08 17:35)
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Complete documentation for dblcens
Functions, R codes and Examples using the dblcens R package
Some associated functions: IVaids . Wdataclean2 . d011 . d011ch . 
Some associated R codes: Wdataclean2.R . d011.R . d011ch.R .  Full dblcens package functions and examples
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