ksigt {ig}R Documentation

Test of Kolmogorov-Smirnov for the IGTD

Description

The function ksigt gives the values for the Kolmogorov-Smirnov (KS) test assuming an IGTD with parameters mu, lambda and an specific kernel. In addition, optionally, this function allows one to obtain a comparative graph between the empirical and theoretical cdfs for a given data set.

Usage

  ksigt(x, kernel = "normal", graph = FALSE, 
        mainTitle = "Cumulative distribution function", xLabel = "data", 
        yLabel = "cdf")

Arguments

x Vector of observations.
kernel Kernel of the pdf of the associated symmetrical distribution by means of which the IGTD is obtained. The kernels: "laplace", "logistic", "normal" and "t" are available.
graph Logical; if TRUE (default), the cdf plot is provided.
mainTitle Main title of the graph.
xLabel A title for the x axis.
yLabel A title for the y axis.

Details

The Kolmogorov-Smirnov test is a goodness-of-fit technique based on the maximum distance between the empirical and theoretical cdfs.

Value

The function ksigt() carries out de Kolmogorov-Smirnov test for the IGTD.

Author(s)

Víctor Leiva <victor.leiva@uv.cl; victor.leiva@yahoo.com>,
Hugo Hernández <hugo.hernandez.p@gmail.com> and
Antonio Sanhueza <asanhueza@ufro.cl>.

References

Sanhueza, A., Leiva, V., Balakrishnan, N. (2008). A new class of inverse Gaussian type distributions. Metrika (in press).

Examples

## Generates a sample from the IGTD with normal kernel 
x <- rigt(300, mu = 1.0, lambda = 1.0, kernel = "normal")

## Produces a KS test abd produces a graph for the IGTD with normal kernel
  ksigt(x, kernel = "normal", graph = TRUE,
        xLabel = "Data",
        yLabel = "Cumulative distribution function")

[Package ig version 1.2 Index]