plot.bootcoefs: Plot the distribution of the bootstrap estimates

In complmrob: Robust Linear Regression with Compositional Data as Covariates

Description

Plot the distribution of the bootstrap estimates and the confidence intervals for the estimates

Usage

## S3 method for class 'bootcoefs'
plot(x, y = NULL, conf.level = 0.95,
  conf.type = "perc", kernel = "gaussian", adjust = 1,
  which = "all", theme = theme_bw(), confStyle = list(color =
  "#56B4E9", alpha = 0.4), estLineStyle = list(color = "black", width =
  rel(1), alpha = 1, linetype = "dashed"), densityStyle = list(color =
  "black", width = rel(0.5), alpha = 1, linetype = "solid"), ...)

Arguments

x	the object returned by a call to the bootcoefs function.
y	ignored.
conf.level	the level of the confidence interval that is plotted as shaded region under the density estimate.
conf.type	the confidence interval type, see boot.ci for details.
kernel	the kernel used for density estimation, see density for details.
adjust	see density for details.
which	which parameters to plot
theme	the ggplot2 theme to use for the plot.
confStyle	a list with style parameters for the confidence region below the density estimate (possible entries are color, and alpha)
estLineStyle	a list with style parameters for the line at the original parameter estimate (possible entries are color, width, alpha, and linetype)
densityStyle	a list with style parameters for the line of the density estimate (possible entries are color, width, alpha, and linetype)
...	ignored

See Also

confint to get the numerical values for the confidence intervals

Examples

data <- data.frame(lifeExp = state.x77[, "Life Exp"], USArrests[ , -3])
mUSArr <- complmrob(lifeExp ~ ., data = data)
bc <- bootcoefs(mUSArr, R = 200) # this can take some time
plot(bc) # for the model diagnostic plots

complmrob documentation built on Sept. 18, 2019, 1:02 a.m.