khazard: Kernel estimate of hazard function for right-censored data

In kernhaz: Kernel Estimation of Hazard Function in Survival Analysis

Description

Kernel estimate of (unconditional) hazard function for right-censored data. Options include two methods for bandwidth selection.

Usage

khazard(times, delta, h = NULL, t = NULL, t.length = 100,
  tmin = NULL, tmax = NULL, kernel = "epanechnikov",
  type = "interior", parallel = FALSE, value = "CVML",
  h.method = "crossval", optim.method = "optimize",
  tol = ifelse(h.method == "crossval", 10^(-6), 1), run = 2, ...)

Arguments

times	vector of observed times
delta	vector of censoring indicator. 0 - censored, 1 - uncensored (dead)
h	bandwidth (scalar or vector). If missing, h is found using some bandwidth selection method.
t	vector of time points at which estimate is evaluated
t.length	number of grid points
tmin, tmax	minimum/maximum values for grid
kernel	kernel function, possible values are: "epanechnikov" (default), "gaussian", "rectangular", "quartic".
type	Type of kernel estimate. Possible types are: "exterior", "interior" (default).
parallel	allows parallel computation. Default is FALSE.
value	If h parameter is vector, this option controls output values. If "CVML" (default), the crossvalidation or log-likelihood values only are calculated. If "hazard", the hazard functions only are calculated. If "both" the crossvalidation or log-likelihood values and hazard function are calculated.
h.method	method for bandwidth selection. Possible methods are: "crossval" (default), "maxlike".
optim.method	method for numerical optimization of the crossvalidation or log-likelihood function. Possible methods are: "optimize" (default), "ga".
tol	the desired accuracy of optimization algorithm
run	the number of consecutive generations without any improvement in the best fitness value before the GA is stopped.
...	additional arguments of GA algorithm

Details

External type of kernel estimator is defined as the ratio of kernel estimator of the subdensity of the uncensored observations to the survival function of the observable time. Internal type of kernel estimator is based on a convolution of the kernel function with a nonparametric estimator of the cumulative hazard function (Nelson-Aalen estimator).

Value

Returns an object of class 'khazard' which is a list with fields

time.points	vector of time points at which estimate is evaluated
hazard	data frame of time points, hazard function values and bandwidth
h	bandwidth
CVML	value of crossvalidation or log-likelihood at h
details	description of used methods
GA.result	output of ga, object of class ga-class

References

Selingerova, I., Dolezelova, H., Horova, I., Katina, S., and Zelinka, J. (2016). Survival of Patients with Primary Brain Tumors: Comparison of Two Statistical Approaches. PloS one, 11(2), e0148733.

See Also

plot.khazard, ga, optimize

Examples

library(survival)
fit<-khazard(times = lung$time,delta = lung$status-1)

Example output

Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl.init' failed, running with 'rgl.useNULL = TRUE'. 

kernhaz documentation built on May 1, 2019, 9:19 p.m.