Plot Individual Time Profiles
Usage
plot.iprofile(z, nind=1, obs=TRUE, add=FALSE, plotsd=FALSE, lty=NULL,
pch=NULL, ylab="Recursive fitted value", xlab="Time",
main=NULL, ylim=NULL, xlim=NULL, ...)
Arguments
z
|
An object of class recursive, from carma ,
gar , kalcount , kalseries ,
kalsurv , or nbkal .
|
nind
|
Observation number(s) of individual(s) to be plotted.
|
obs
|
If TRUE, plots observed responses.
|
add
|
If TRUE, the graph is added to an existing plot.
|
plotsd
|
If TRUE, plots standard deviations around profile
(carma only).
|
others
|
Plotting control options.
|
Value
plot.iprofile
is used for plotting individual profiles over time
for models obtained from Kalman fitting. See
plot.profile
for plotting marginal profiles.Author(s)
J.K. LindseySee Also
carma
, gar
, kalcount
,
kalseries
, kalsurv
, nbkal
plot.profile
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)