| profile(rmutil) | R Documentation |
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", ...)
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. |
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.
J.K. Lindsey
carma, elliptic, gar,
kalcount, kalseries,
kalsurv, nbkal iprofile,
plot.residuals.
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)