eg4parm: Generated 4 Parameter Logistic Data

In kloke/npsmReg2: R functions for Chapter 7 of Nonparametric Statistical Methods Using R

Description

This is the generated data set from a nonlinear 4-parameter logistic model which is discussed in Example 7.7.3, page 210, of Kloke and McKean (2014).

Usage

data("eg4parm")

Format

Twenty-four observations on three variables.

x

predictor

y1

original response

y2

changed response

References

Kloke, J. and McKean, J.W. (2014), Nonparametric statistical methods using R, Boca Raton, FL: Chapman-Hall.

Examples

data(eg4parm)
data <- eg4parm

func <- function(z,theta){
     d = theta[1]; s = theta[2]; c = theta[3]; b = theta[4]
     func <- (s/(1 + exp(b*(z*log(10) - log(c))))) + d
     func
}
jake = function(z,theta){
     d = theta[1]; s = theta[2]; c = theta[3]; b = theta[4]
     xp = 1 + exp(b*(z*log(10) - log(c)))
     fd = 1; fs = 1/xp
     fc = s*(xp^(-2))*((b/c)*exp(b*(z*log(10) - log(c))))
     fb = -s*(xp^(-2))*((z*log(10) - log(c))*exp(b*(z*log(10) - log(c))))
     jake = cbind(fd,fs,fc,fb); jake
}

a <- 10; b <- -1.2; c <- 3; d <- 110; s <- -100;
z <- log10(data[,1]); z <- matrix(z,ncol=1); y<-data[,2]
theta0 = c(d,s,c,b); # theta0<-matrix(theta0,ncol=1)

fitwil = wilnl(z,y, theta0,func,jake,intercept=TRUE)
summary(fitwil)

kloke/npsmReg2 documentation built on May 20, 2019, 12:34 p.m.