qtplot.gumbel: Quantile Plot for Gumbel Regression

Description Usage Arguments Details Value Note Author(s) See Also Examples

View source: R/qtplot.q

Description

Plots quantiles associated with a Gumbel model.

Usage

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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

See Also

gumbel.

Examples

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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
Loading required package: splines
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.