`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.

1 2 3 |

`x` |
An object of class |

`nind` |
Observation number(s) of individual(s) to be plotted. (Not
used if |

`intensity` |
If TRUE, the intensity is plotted instead of the time
between events. Only for models produced by |

`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. |

`mprofile`

returns information ready for plotting by
`plot.mprofile`

.

J.K. Lindsey

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
## 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)
``` |

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