Produce Marginal Time Profiles for Plotting
Usage
plot(profile(z, times=NULL, mu=NULL, ccov, plotse=F), nind=1,
intensity=F, add=FALSE, ylim=c(min(z$pred),max(z$pred)),
lty=NULL, ylab="Fitted value", xlab="Time", ...)
Arguments
z
|
An object of class recursive, from carma ,
elliptic , gar , kalcount ,
kalseries , kalsurv , or nbkal .
|
times
|
Vector of time points at which profiles are to be plotted.
|
mu
|
The location regression as a function of the parameters and
the times, for the desired covariate values.
|
ccov
|
Covariate values for the profiles (carma
only).
|
plotse
|
Plot standard errors (carma only).
|
nind
|
Observation number(s) of individual(s) to be plotted. (Not
used if mu is supplied.)
|
intensity
|
If z has class, kalsurv , and this is TRUE, the
intensity is plotted instead of the time between events.
|
add
|
If TRUE, add contour to previous plot instead of creating a
new one.
|
others
|
Plotting control options.
|
Value
profile
is used for plotting marginal profiles over time
for models obtained from Kalman fitting, for given fixed values of
covariates. See iprofile
for plotting individual
profiles.Author(s)
J.K. LindseySee Also
carma
, elliptic
, gar
,
kalcount
, kalseries
,
kalsurv
, nbkal
iprofile
,
plot.residuals
.Examples
library(repeated)
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)