This function provides survival estimates using the product-limit
Kaplan-Meier estimator.

Provides estimates for the bivariate and trivariate distribution
functions and bivariate and trivariate survival functions for
censored gap times. Two approaches, using existing methodologies,
are considered: (i) the Lin's estimator, which is based on the
extension the Kaplan-Meier estimator of the distribution function
for the first event time and the Inverse Probability of Censoring
Weights for the second time (Lin DY, Sun W, Ying Z (1999)
<doi:10.1093/biomet/86.1.59> and (ii) another estimator
based on Kaplan-Meier weights (Una-Alvarez J, Meira-Machado L (2008)
<https://w3.math.uminho.pt/~lmachado/Biometria_conference.pdf>).
The proposed methods are the landmark estimators based on
subsampling approach, and the estimator based on weighted cumulative
hazard estimator. The package also provides nonparametric estimator
conditional to a given continuous covariate. All these methods have
been submitted to be published.

Gustavo Soutinho

survivalREC

Nonparametric Estimation of the Distribution of Gap Times for
Recurrent Events

Luis Meira-Machado

Artur Araujo

Ana Moreira

KM function

<dl><dt>time</dt>
<dd>Survival time of the process.</dd>
<dt>status</dt>
<dd>Censoring indicator of the survival time of the process; 0 if 
the survival time is censored and 1 otherwise.</dd>
<dt>t</dt>
<dd>The time for obtaining survival estimates.</dd></dl>

Arguments

Gustavo Soutinho and Luis Meira-Machado

Author

Kaplan-Meier product-limit estimate of survival — KM

<dl>

<dt>time</dt>
<dd>Survival time of the process.</dd>


<dt>status</dt>
<dd>Censoring indicator of the survival time of the process; 0 if 
the survival time is censored and 1 otherwise.</dd>


<dt>t</dt>
<dd>The time for obtaining survival estimates.</dd>

</dl>

KM: Kaplan-Meier product-limit estimate of survival

Description

Usage

Value

Arguments

Author

References

Examples