tauhat_func: Kernel-based Local Kaplan-Meier Estimator for the Conditional...

In QTOCen: Quantile-Optimal Treatment Regimes with Censored Data

Description

This function estimates the value of

F(T <= y_0 \mid x_0),

the conditional cumulative distribution function of a survival time T given covaraites vector x_0 at value y_0. This estimator is described in detail in \insertCitewang2009locallyQTOCen.

Usage

tauhat_func(y0, x0, z, x, delta, bw)

Arguments

y0	the vector of censored outcome of a single observation
x0	the vector of given covariate of a single observation
z	observed vector of response variable from observed data
x	the observed matrix of covariates, the dimension is # of observations by number of covariates. Note that the vector of ones should NOT be included in x.
delta	the vector of censoring indicators
bw	the scalar bandwidth parameter in kernel

Details

For cases with multivariate covariates, we adopted a product kernel. For example, in the bivariate case we use

K(x_1, x_2) = K_1(x_1) K_2(x_2),

where K_1 and K_2 are both biquadratickernel functions.

References

\insertRef

wang2009locallyQTOCen

Examples

tauhat_func(y0=10, x0=c(2,3), z=c(10, 12, 11), 
            x=matrix(c(1,1,2,2,3,3), nrow=3, byrow=TRUE), 
            delta=c(1,1,0), bw=10)

QTOCen documentation built on June 4, 2019, 5:03 p.m.