lpl.control: Auxiliary function for lpl fitting

In statapps/lpl: Local Partial Likelihood Estimation and Simultaneous Confidence Band

Description

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

Usage

#   lpl.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 lpl.

Value

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

Author(s)

Siwei Zhang and Bingshu E. Chen

See Also

lplb, lple

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 lpl model with some control variables changed, 

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

## then fit the following model

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

statapps/lpl documentation built on Dec. 23, 2021, 5:27 a.m.