# qtplot.gumbel: Quantile Plot for Gumbel Regression In VGAM: Vector Generalized Linear and Additive Models

## Description

Plots quantiles associated with a Gumbel model.

## Usage

 ```1 2 3 4 5 6 7 8``` ```qtplot.gumbel(object, show.plot = TRUE, y.arg = TRUE, spline.fit = FALSE, label = TRUE, R = object@misc\$R, percentiles = object@misc\$percentiles, add.arg = FALSE, mpv = object@misc\$mpv, xlab = NULL, ylab = "", main = "", pch = par()\$pch, pcol.arg = par()\$col, llty.arg = par()\$lty, lcol.arg = par()\$col, llwd.arg = par()\$lwd, tcol.arg = par()\$col, tadj = 1, ...) ```

## Arguments

 `object` A VGAM extremes model of the Gumbel type, produced by modelling functions such as `vglm` and `vgam`, and with a family function that is either `gumbel` or `gumbelff`. `show.plot` Logical. Plot it? If `FALSE` no plot will be done. `y.arg` Logical. Add the raw data on to the plot? `spline.fit` Logical. Use a spline fit through the fitted percentiles? This can be useful if there are large gaps between some values along the covariate. `label` Logical. Label the percentiles? `R` See `gumbel`. `percentiles` See `gumbel`. `add.arg` Logical. Add the plot to an existing plot? `mpv` See `gumbel`. `xlab` Caption for the x-axis. See `par`. `ylab` Caption for the y-axis. See `par`. `main` Title of the plot. See `title`. `pch` Plotting character. See `par`. `pcol.arg` Color of the points. See the `col` argument of `par`. `llty.arg` Line type. Line type. See the `lty` argument of `par`. `lcol.arg` Color of the lines. See the `col` argument of `par`. `llwd.arg` Line width. See the `lwd` argument of `par`. `tcol.arg` Color of the text (if `label` is `TRUE`). See the `col` argument of `par`. `tadj` Text justification. See the `adj` argument of `par`. `...` Arguments passed into the `plot` function when setting up the entire plot. Useful arguments here include `sub` and `las`.

## Details

There should be a single covariate such as time. The quantiles specified by `percentiles` are plotted.

## Value

The object with a list called `qtplot` in the `post` slot of `object`. (If `show.plot = FALSE` then just the list is returned.) The list contains components

 `fitted.values` The percentiles of the response, possibly including the MPV. `percentiles` The percentiles (small vector of values between 0 and 100.

## Note

Unlike `gumbel`, one cannot have `percentiles = NULL`.

## Author(s)

Thomas W. Yee

`gumbel`.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```ymat <- as.matrix(venice[, paste("r", 1:10, sep = "")]) fit1 <- vgam(ymat ~ s(year, df = 3), gumbel(R = 365, mpv = TRUE), data = venice, trace = TRUE, na.action = na.pass) head(fitted(fit1)) ## Not run: par(mfrow = c(1, 1), bty = "l", xpd = TRUE, las = 1) qtplot(fit1, mpv = TRUE, lcol = c(1, 2, 5), tcol = c(1, 2, 5), lwd = 2, pcol = "blue", tadj = 0.4, ylab = "Sea level (cm)") qtplot(fit1, perc = 97, mpv = FALSE, lcol = 3, tcol = 3, lwd = 2, tadj = 0.4, add = TRUE) -> saved head(saved@post\$qtplot\$fitted) ## End(Not run) ```

### Example output ```Loading required package: stats4
VGAM  s.vam  loop  1 :  loglikelihood = -1137.5884
VGAM  s.vam  loop  2 :  loglikelihood = -1088.6181
VGAM  s.vam  loop  3 :  loglikelihood = -1079.7142
VGAM  s.vam  loop  4 :  loglikelihood = -1078.882
VGAM  s.vam  loop  5 :  loglikelihood = -1078.7252
VGAM  s.vam  loop  6 :  loglikelihood = -1078.713
VGAM  s.vam  loop  7 :  loglikelihood = -1078.7071
VGAM  s.vam  loop  8 :  loglikelihood = -1078.707
VGAM  s.vam  loop  9 :  loglikelihood = -1078.7066
VGAM  s.vam  loop  10 :  loglikelihood = -1078.7066
95%      99%      MPV
1 68.17273 90.04047 112.6121
2 68.46769 90.29102 112.8168
3 68.76404 90.54248 113.0219
4 69.05527 90.78985 113.2240
5 69.33842 91.03085 113.4215
6 69.61724 91.26808 113.6158
97%
1 75.11341
2 75.39428
3 75.67638
4 75.95369
5 76.22346
6 76.48908
```

VGAM documentation built on Jan. 16, 2021, 5:21 p.m.