DnE (version 2.1.0)

is.nbinom: is.nbinom

Description

judge if the data obeys negative binomial distribution

Usage

is.nbinom(x, m, a, p0 = NULL, r0 = NULL)

Arguments

x

data

m

the number of intervals you want to divide the data in, default value is 10

a

significance level

p0

the pobability of success in each experiment

r0

the number of successful events you want to wait for

Value

Details

Given a set of observations from a certain distribution, this function is used to test whether the observations are from a distribution of negative binomial distribution or not. Usually, to ensure the function works well, the sample size needs to be large enough, i.e. the result will be stable if the sample size is larger than 100. The function will work better if the number of intervals you choose to divide the data in is between 10 and 20. This number cannot excess the number of given oberservations.

References

ROBERT V. HOGG/ALLEN T. CRAIG (Fifth Edition) Introduction Mathematical Statistics.

See Also

is.dt , DnE-package

Examples

require(stats)
examplecheck<-rnbinom(100,10,0.1)
is.nbinom(examplecheck,10,0.05)
##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.