iprofile {rmutil} | R Documentation |
plot(iprofile(z, plotsd=FALSE), nind=1, observed=TRUE, intensity=F, add=FALSE, lty=NULL, pch=NULL, ylab=NULL, xlab=NULL, main=NULL, ylim=NULL, xlim=NULL, ...)
z |
An object of class recursive, from carma ,
elliptic , gar , kalcount ,
kalseries , kalsurv , or nbkal . |
plotsd |
If TRUE, plots standard deviations around profile
(carma and elliptic only). |
nind |
Observation number(s) of individual(s) to be plotted. |
observed |
If TRUE, plots observed responses. |
intensity |
If z has class, kalsurv , and this is TRUE, the
intensity is plotted instead of the time between events. |
add |
If TRUE, the graph is added to an existing plot. |
others |
Plotting control options. |
iprofile
is used for plotting individual profiles over time
for models obtained from Kalman fitting. See profile
for
plotting marginal profiles.
J.K. Lindsey
carma
, elliptic
, gar
,
kalcount
, kalseries
,
kalsurv
, nbkal
profile
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)