Nonparametric Estimation of the Distribution of Gap Times for Recurrent Events
Estimation of the conditional distribution function of the response, g...
Inverse probability of censoring weighting estimator for the bivariate...
Kaplan-Meier product-limit estimate of survival
Kaplan-Meier weights
Kaplan-Meier Weighted estimator for three gap times distribution funct...
Kaplan-Meier Weighted estimator for the bivariate distribution functio...
Landmark estimator for three gap times distribution function.
Landmark estimator for the bivariate distribution function
Lin's estimator for three gap times distribution function.
Lin's estimator for the bivariate distribution function.
Create a multidf object
Nadaraya-Watson weights
Plot methods for a multidf object
Weighted cumulative hazard estimator for three gap times distribution ...
Weighted cumulative hazard estimator for the bivariate distribution fu...
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.