dbEmpLikeNorm (version 1.0.0)

dbELnorm: Goodness of Fit Test for Normality Among Multiple Groups

Description

Performs density based empirical likelihood goodness of fit tests for normality among multiple groups

Usage

dbELnorm(x, delta=0.05, num.mc=1000, pvl.Table=TRUE, vrb=TRUE)

Arguments

x

list of groups or experiments

delta

an option for changing the minimizing range for the EL ratio test statistic

num.mc

number of simulations to use when calculating p-value

pvl.Table

logical indicating if p-value should be calculated based on estimates from stored data tables or by using Monte Carlo techniques

vrb

logical indicating if status messages should be printed

Value

Returns a vector of length 2 with test statistic and p-value.

teststat

the value of the test statistic

pvalue

the p-value for the test

Details

The method employs a density-based empirical likelihood approach to obtain the test statistic and p-values for a goodness-of-fit tests for normality. The null distribution is that the data in x is normally distributed with possibly different means and standard deviations.

'x' is a list object where each item in the list is a different set of data.

The 'delta' value must be in the range [0,1]. Essentially this setting controls the range over which a minimum is taken to produce the EL ratio test statistic. The range is from 1 to n^(1-'delta') where 'n' represents the number of observations in 'x'.

The 'pvl.Table' is a binary option where when TRUE, the p-value for the test statistic is determined by imputation from a stored table of test statistics and significance levels for common sample sizes. If 'pvl.Table' is FALSE, then the p-value is determined from Monte-Carlo simulations where the number of resamplings is set by 'num.mc'.

References

Tsai WM, Shepherd LA, Miecznikowski J, Hutson A, Vexler A. (2013). An EL based test for normality in multiple groups. Department of Biostatistics. University at Buffalo. Report 1204.

Examples

x = rnorm(30, 3,1)
y = rnorm(40, 4,1)

Lst = list(x,y)
dbELnorm(Lst)

y = runif(40)
Lst = list(x,y)
dbELnorm(Lst)