# iprofile: Produce Individual Time Profiles for Plotting In swihart/rmutil: Utilities for Nonlinear Regression and Repeated Measurements Models

## Description

`iprofile` is used for plotting individual profiles over time for objects obtained from dynamic models. It produces output for plotting recursive fitted values for individual time profiles from such models.

See `mprofile` for plotting marginal profiles.

## Usage

 ```1 2 3 4``` ```## S3 method for class 'iprofile' plot(x, nind=1, observed=TRUE, intensity=FALSE, add=FALSE, lty=NULL, pch=NULL, ylab=NULL, xlab=NULL, main=NULL, ylim=NULL, xlim=NULL, ...) ```

## Arguments

 `x` An object of class `iprofile`, e.g. `x = iprofile(z, plotsd=FALSE)`, where `z` is an object of class `recursive`, from `carma`, `elliptic`, `gar`, `kalcount`, `kalseries`, `kalsurv`, or `nbkal`. If `plotsd` is 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.
 `lty,pch,main,ylim,xlim,xlab,ylab` See base plot. `...` Arguments passed to other functions.

## Value

`iprofile` returns information ready for plotting by `plot.iprofile`.

## Author(s)

J.K. Lindsey

`mprofile` `plot.residuals`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```## Not run: ## try this after you have repeated package installed 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,scale=mu(log(c(1,0.3,0.2)))),ncol=20,byrow=TRUE) conc[,2:20] <- conc[,2:20]+0.5*(conc[,1:19]-matrix(mu(log(c(1,0.3,0.2))), ncol=20,byrow=TRUE)[,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(mprofile(z), nind=1:2, lty=1:2, add=TRUE) ## End(Not run) ```