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. LindseySee 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)