wil1stp02: Rank-Based Nonlinear Subroutine

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

Description

Subroutine that computes the rank-based fit for each iterative step in the rank-based nonlinear fit function wilnl.R.

Usage

wil1stp02(x, y, theta0, fmodel, jmodel, wts.type = "WIL", intest = "HL", intercept = FALSE)

Arguments

x	matrix of predictors
y	response vector
theta0	initial estimate of parameters used at the beginning of the step
fmodel	the function that computes the nonlinear model
jmodel	the function that computes the jacobian
wts.type	either “WIL” (default) for the Wilcoxon fit of “HBR” for the HBR fit.
intest	for the estimate of the intercept: “HL” (default) computes the Hodges-Lehmann estimate based on the residuals and “MED” computes the median of the residuals.
intercept	TRUE if an intercept is in the nonlinear model else FALSE (default).

Value

theta1	new estimate of nonlinear parameters
delstar	theta1 minus theta0
resid0	residual at end of step
sse0	sum of squared errors for initial fit
sse1	sum of squared errors for final (at end of the step) fit

Author(s)

Joe McKean ([e-mail]) and John Kloke ([e-mail])

References

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

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