R: Produce Marginal Time Profiles for Plotting

mprofile {rmutil} | R Documentation

## Produce Marginal Time Profiles for Plotting

### Description

`mprofile` is used for plotting marginal profiles over time for models obtained from dynamic models, for given fixed values of covariates. These are either obtained from those supplied by the model, if available, or from a function supplied by the user.

See `iprofile` for plotting individual profiles from recursive fitted values.

### Usage

    ## S3 method for class 'mprofile'
    plot(x, nind=1, intensity=FALSE, add=FALSE, ylim=range(z$pred, na.rm = TRUE),
    	lty=NULL, ylab=NULL, xlab=NULL, ...)

### Arguments

`x` | An object of class `mprofile`, e.g. `x = mprofile(z, times=NULL, mu=NULL, ccov, plotse=TRUE)`, where `z`An object of class `recursive`, from `carma`, `elliptic`, `gar`, `kalcount`, `kalseries`, `kalsurv`, or `nbkal`; `times` is a vector of time points at which profiles are to be plotted; `mu` is the location regression as a function of the parameters and the times for the desired covariate values; `ccov` is covariate values for the profiles (`carma` only); and `plotse` when TRUE plots standard errors (`carma` only).
`nind` | Observation number(s) of individual(s) to be plotted. (Not used if `mu` is supplied.)
`intensity` | If TRUE, the intensity is plotted instead of the time between events. Only for models produced by `kalsurv`.
`add` | If TRUE, add contour to previous plot instead of creating a new one.

`lty,ylim,xlab,ylab` | See base plot.
`...` | Arguments passed to other functions.

### Value

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

### Author(s)

J.K. Lindsey

### See Also

`iprofile`, `plot.residuals`.

### Examples

    ## Not run:
    ## try after you get the repeated package
    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)

[Package rmutil version 1.1.3 Index]