profilelike.gls {ProfileLikelihood}

Profile Likelihood for Linear Models for Longitudinal Responses Fitted by Generalized Least Squares

Description

This function provides values for a profile likelihood and a normalized profile likelihood for a parameter of interest in a linear model for longitudinal responses fitted by generalized least squares.

Usage

profilelike.gls(formula, data, correlation = NULL, subject, profile.theta, 
		method = "ML", lo.theta, hi.theta, length = 300, round = 2, 
		subset = NULL, weights = NULL, ...)

Arguments

formula

see corresponding documentation in gls.

data

a data frame. See corresponding documentation in gls.

correlation

see corresponding documentation in gls.

subject

see corresponding documentation in gls.

profile.theta

a parameter of interest, theta; must be a numeric variable.

method

see corresponding documentation in gls.

lo.theta

lower bound for a parameter of interest to obtain values for a profile likelihood.

hi.theta

upper bound for a parameter of interest to obtain values for a profile likelihood.

length

length of numerical grid values for a parameter of interest to obtain values for a profile likelihood.

round

the number of decimal places for round function to automatically define lower and upper bounds of numerical grid for a parameter of interest. If an automatically defined parameter range is not appropriate, increase the number or specify lo.theta and hi.theta.

subset

should not be provided.

weights

should not be provided.

...

further arguments passed to or from other methods.

Details

This function provides values for a profile likelihood and a normalized profile likelihood for a parameter of interest in a linear model for longitudinal responses fitted by generalized least squares. Users must define a parameter of interest in the model. This function can be used for models for longitudinal responses comparable with the gls function. However, arguments weights and subset should not be provided. A normalized profile likelihood is obtained by a profile likelihood being divided by the maximum value of the profile likelihood so that a normalized profile likelihood ranges from 0 to 1.

Value

theta

numerical grid values for a parameter of interest in a specified range (between lower and upper bounds).

profile.lik

numerical values for a profile likelihood corresponding to theta in a specified range (between lower and upper bounds).

profile.lik.norm

numerical values for a normalized profile likelihood ranging from 0 to 1.

Warning

Arguments weights and subset in the gls function are not comparable.

Missing values should be removed.

Author(s)

Leena Choi <[e-mail]>

See Also

profilelike.plot, profilelike.summary, profilelike.lm, profilelike.glm, profilelike.polr, profilelike.lme, gls

Examples

data(Gasoline, package = "nlme")
xx <- profilelike.gls(formula=yield ~ endpoint, correlation=nlme::corAR1(form = ~ 1 | id),
	data=Gasoline, subject="Sample", profile.theta="vapor", method="ML", 
	lo.theta=1, hi.theta=5, length=500, round=2)
profilelike.plot(theta=xx$theta, profile.lik.norm=xx$profile.lik.norm, round=4)