# plot.residuals: Plot Residuals In rmutil: Utilities for Nonlinear Regression and Repeated Measurements Models

 plot.residuals R Documentation

## Plot Residuals

### Description

`plot.residuals` is used for plotting residuals from models obtained from dynamic models for given subsets of the data.

### Usage

```## S3 method for class 'residuals'
plot(x, X=NULL, subset=NULL, ccov=NULL, nind=NULL,
recursive=TRUE, pch=20, ylab="Residual", xlab=NULL,
main=NULL, ...)
```

### Arguments

 `x` An object of class recursive, from `carma`, `gar`, `kalcount`, `kalseries`, `kalsurv`, or `nbkal`. `X` Vector of of values for the x-axis. If missing, time is used. It can also be specified by the strings "response" or "fitted". `subset` A logical vector defining which observations are to be used. `ccov` If the name of a time-constant covariate is supplied, separate plots are made for each distinct value of that covariate. `nind` Observation number(s) of individual(s) to be plotted. `recursive` If TRUE, plot recursive residuals, otherwise ordinary residuals. `pch,ylab,xlab,main,...` Plotting control options.

### Author(s)

J.K. Lindsey

`carma`, `gar`, `kalcount`, `kalseries`, `kalsurv`, `nbkal` `plot.iprofile`, `plot.mprofile`.

### Examples

```## Not run:
library(repeated)
times <- rep(1:20,2)
dose <- c(rep(2,20),rep(5,20))
mu <- function(p) exp(p-p)*(dose/(exp(p)-exp(p))*
(exp(-exp(p)*times)-exp(-exp(p)*times)))
shape <- function(p) exp(p-p)*times*dose*exp(-exp(p)*times)
conc <- matrix(rgamma(40,2,scale=mu(log(c(1,0.3,0.2)))/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=0.1, pshape=log(c(1,0.2)))
plot.residuals(z, subset=1:20, main="Dose 1")
plot.residuals(z, x="fitted", subset=1:20, main="Dose 1")
plot.residuals(z, x="response", subset=1:20, main="Dose 1")

## End(Not run)
```

rmutil documentation built on Oct. 29, 2022, 1:08 a.m.