Plot Marginal Time Profiles

Usage

plot.profile(z, times=NULL, nind=1, mu=NULL, add=FALSE, ylim=NULL,
	lty=NULL, ylab="Fitted value", xlab="Time", ...)

Arguments

z An object of class recursive, from carma, gar, kalcount, kalseries, kalsurv, or nbkal.
times Vector of time points at which profiles are to be plotted.
nind Observation number(s) of individual(s) to be plotted.
mu The location regression as a function of the parameters and the times, for the desired covariate values.
add If TRUE, add contour to previous plot instead of creating a new one.
others Plotting control options.

Value

plot.profile is used for plotting marginal profiles over time for models obtained from Kalman fitting, for given fixed values of covariates. See plot.iprofile for plotting individual profiles.

Author(s)

J.K. Lindsey

See Also

carma, gar, kalcount, kalseries, kalsurv, nbkal plot.iprofile, plot.residuals.

Examples

times <- rep(1:20,2)
dose <- c(rep(2,20),rep(5,20))
mu <- function(p) exp(p[1]-p[3])*(dose/(exp(p[1])-exp(p[2]))*
	(exp(-exp(p[2])*times)-exp(-exp(p[1])*times)))
shape <- function(p) exp(p[1]-p[2])*times*dose*exp(-exp(p[1])*times)
conc <- matrix(rgamma(40,1,mu(log(c(1,0.3,0.2)))),ncol=20,byrow=T)
conc[,2:20] <- conc[,2:20]+0.5*(conc[,1:19]-matrix(mu(log(c(1,0.3,0.2))),
	ncol=20,byrow=T)[,1:19])
conc <- ifelse(conc>0,conc,0.01)
z <- gar(conc, dist="gamma", times=1:20, mu=mu, shape=shape,
	preg=log(c(1,0.4,0.1)), pdepend=0.5, pshape=log(c(1,0.2)))
# plot individual profiles and the average profile
plot.iprofile(z, nind=1:2, pch=c(1,20), lty=3:4)
plot.profile(z, nind=1:2, lty=1:2, add=T)


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