evd (version 2.3-3)

plot.profile.evd: Plot Profile Log-likelihoods and Calculate Profile Confidence Intervals

Description

Displays profile log-likelihoods from a model profiled with profile.evd, and invisibly returns profile confidence intervals.

Usage

# S3 method for profile.evd
plot(x, which = names(x), main = NULL,
    ask = nb.fig < length(which) && dev.interactive(), ci = 0.95,
    clty = 2, …)

Arguments

x

An object of class "profile.evd".

which

A character vector giving the parameters for which the profile deviance is plotted, and for which profile confidence intervals are calculated. By default all profiled parameters in x are used.

main

Title of each plot; a character vector, the same length as which.

ask

Logical; if TRUE, the user is asked before each plot.

ci

A numeric vector. For each parameter in which profile confidence intervals are calculated, for each confidence coefficient in ci (but see Warning). The intervals are returned invisibly as a list of vectors/matrices. Each plot then (by default) includes horizonal lines that represent each interval.

clty

The line type of the horizontal lines that represent the profile confidence intervals. To omit the lines set clty to zero.

…

Other graphics parameters.

Value

Profile devainces are plotted for each parameter in which. A list with one element for each parameter in which is also returned invisibly. Each element is a vector of length two or a matrix with two columns, giving the lower and upper limits of each confidence interval.

Warning

The profile confidence intervals may not have confidence coefficient ci, because the usual asymptotic properties of maximum likelihood estimators may not hold. For the GEV model, the usual asymptotic properties hold when the shape parameter is greater than \(-0.5\) (Smith, 1985).

References

Smith, R. L. (1985) Maximum likelihood estimation in a class of non-regular cases. Biometrika, 72, 67--90.

See Also

plot.profile2d.evd, profile.evd, profile2d.evd

Examples

# NOT RUN {
uvdata <- rgev(100, loc = 0.13, scale = 1.1, shape = 0.2)
M1 <- fgev(uvdata)
# }
# NOT RUN {
M1P <- profile(M1)
# }
# NOT RUN {
par(mfrow = c(2,2))
# }
# NOT RUN {
cint <- plot(M1P, ci = c(0.95, 0.99))
# }
# NOT RUN {
cint
# }