lplb.control: Auxiliary function for lplb fitting

In statapps/lplb: Local Partial Likelihood Bootstrap (LPLB) test

Description

Auxiliary function for lplb fitting. Typically only used internally by 'lplb', but may be used to construct a control argument to either function.

Usage

#   lplb.control(h, kernel = 'gaussian', B, w0, p1, pctl)

Arguments

h	bandwidth of kernel function. The default value is h = 0.2
kernel	kernel funtion types, including "gaussian", "epanechnikov", "rectangular", "triangular", "biweight", "cosine", "optcosine". The default value is 'gaussian'
B	number of bootstrap times. The default value is 200
w0	the estimated points in the interval of (0,1), select arbitrarily. The default value is seq(0.05, 0.95, 0.025)
p1	the number of dependend variables that make interactions with the biomarker w. The default value is 1
pctl	the estimated points that want to be shown in the output. The default value is seq(0.2, 0.8, 0.1)

Details

Control is used in model fitting of lplb.

Value

This function checks the internal consisitency and returns a list of value as inputed to control model fit of lplb.

Author(s)

Siwei Zhang and Bingshu E. Chen

See Also

lplb

Examples

## The default control values are: h = 0.2, kernel = 'gaussian', B = 200, w0 = seq(0.05, 0.95, 0.025), p1 = 1, pctl = seq(0.2, 0.8, 0.1) 
##
## To fit the lplb model with some control variables changed, 

w0=seq(0.03,0.97,by=2/100)
ctl = lplb.control(w0=w0, h=0.3, p1=2, B=100)

## then fit the following model

#fit = lplb(x, y, control = ctl)

statapps/lplb documentation built on July 10, 2021, 6:14 p.m.