# group.plots: Plot function for grouped data In qrNLMM: Quantile Regression for Nonlinear Mixed-Effects Models

## Description

Functions for plotting a profiles plot for grouped data.

## Usage

 ```1 2 3``` ```group.plot(x,y,groups,...) group.lines(x,y,groups,...) group.points(x,y,groups,...) ```

## Arguments

 `y` the response vector of dimension N where N is the total of observations. `x` vector of longitudinal (repeated measures) covariate of dimension N. For example: Time, location, etc. `groups` factor of dimension N specifying the partitions of the data over which the random effects vary. `...` additional graphical arguments passed to `matplot`. See `par`.

## Author(s)

Christian E. Galarza <[email protected]> and Victor H. Lachos <[email protected]>

`Soybean`, `HIV`, `QRNLMM`, `QRLMM`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```## Not run: #A full profile plot for Soybean data data(Soybean) attach(Soybean) group.plot(x = Time,y = weight,groups = Plot,type="b", main="Soybean profiles",xlab="time (days)", ylab="mean leaf weight (gr)") #Profile plot by genotype group.plot(x = Time[Variety=="P"],y = weight[Variety=="P"], groups = Plot[Variety=="P"],type="l",col="blue", main="Soybean profiles by genotype",xlab="time (days)", ylab="mean leaf weight (gr)") group.lines(x = Time[Variety=="F"],y = weight[Variety=="F"], groups = Plot[Variety=="F"],col="black") ## End(Not run) ```