qqgbs {gbs}R Documentation

Quantile versus quantile plot for the the GBSD

Description

The function {qqgbs()} produces a quantile-quantile (QQ) plot for the GBSD based on the MLE of their parameters. Also, a line going through the first and the third quartile can be sketched. In addition, the coefficient of determination of least squares for the fit line is given.

Usage

qqgbs(x, kernel = "normal", line = FALSE, xLabel = "Empirical quantiles", 
      yLabel = "Theoretical quantiles")

Arguments

x Vector of observations.
kernel Kernel of the pdf of the associated symmetrical distribution by means of which the GBSD is obtained. The kernels: laplace, logistic, normal and t are available.
line Logical; if TRUE (default), a line going by the first and third quartile is sketched.
xLabel A title for the x axis.
yLabel A title for the x axis.

Details

The function {qqgbs()} carries out a QQ plot for the GBSD.

Value

The function qqgbs() carries out an graphical plot useful as goodness-of-fit tool.

Author(s)

Barros, Michelli <michelli.karinne@gmail.com>
Leiva, Victor <victor.leiva@uv.cl, victor.leiva@yahoo.com>
Paula, Gilberto A. <giapaula@ime.usp.br>

References

Diaz-Garcia, J.A., Leiva, V. (2005) A new family of life distributions based on elliptically contoured distributions. J. Stat. Plan. Infer. 128:445-457 (Erratum: J. Stat. Plan. Infer. 137:1512-1513).

Leiva, V., Barros, M., Paula, G.A., Sanhueza, A. (2008) Generalized Birnbaum-Saunders distributions applied to air pollutant concentration. Environmetrics 19:235-249.

Sanhueza, A., Leiva, V., Balakrishnan, N. (2008) The generalized Birnbaum-Saunders distribution and its theory, methodology and application. Comm. Stat. Theory and Meth. 37:645-670.

Examples

## Generates a sample from the GBSD with normal kernel
x <- rgbs(300, alpha = 1.0, beta = 1.0,  nu = 1.0, kernel = "normal")

## Produces a QQ plot for the GBSD with normal kernel
qqgbs(x, kernel = "normal", line = TRUE)

[Package gbs version 1.0 Index]