resplot function

Relative distribution plot to a Standard Normal

Relative distribution plot to a Standard Normal

resplot produces a relative distribution of the values to a standard normal.

Graphical parameters may be given as arguments to resplot.

resplot(x, standardize=TRUE, xlab="Gaussian Cumulative Proportion", method="Bayes", ...)

Arguments

  • x: The first sample for resplot.

  • standardize: Should the sample be converted to standard units first?

  • xlab: plot labels.

  • method: Method used to estimate the relative density. The default ("Bayes") uses a density estimator based on Poisson Nonparametric Regression and Bayesian inference developed by Wand and Wu (2022). The option ("bgk") uses a Gaussian kernel density estimator for bounded domain one-dimensional data developed by Botev, Grotowski and Kroese (2010). The option ("gam") uses a local likelihood approach based on smoothed Poisson regression. The option "loclik" uses log-splines. The option "quick" uses the Anscombe transformation to stabilize variances. In versions prior to 1.3 the "quick"

    approach was used.

  • ...: graphical parameters.

Returns

A list with components summarizing the relative distribution. See reldist for the details.

See Also

reldist.

Examples

y <- rnorm(2000) resplot(y, method="bgk") data(precipitation) resplot(precipitation, ylab = "Precipitation [in/yr] for 70 US cities", method="bgk")