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)