is.PD: Test for the shape of the distribution
In PEkit: Partition Exchangeability Toolkit

Description Usage Arguments Details Value References Examples

View source: R/Neutrality_tests.R

This function performs a statistical test on the null hypothesis that a given sample's underlying distribution is the Poisson-Dirichlet distribution. It calculates a test statistic that is then used to gain a p-value from an empirical distribution of the statistic from simulated samples from a PD distribution.

1	is.PD(x, rounds)

`x`	A discrete data vector.
`rounds`	How many samples are simulated to obtain the empirical distribution.

The calculated test statistic is

W=∑_{i=1}^n n_i^2 / n ,

which is calculated from the sample. Here n_i are the frequencies of each unique value in the sample. The MLE of ψ is then estimated from the sample with the function MLEp(), and an amount of samples equal to the input parameter rounds are generated with that estimate of ψ and sample size n. The test statistic W is then calculated for each of the simulated samples. The original W is then given a p-value based on what percentage of the simulated W it exceeds.

A p-value.

Watterson, G.A., (1978), The homozygosity test of neutrality. Genetics. 88(2):405-417.

##Test whether a typical sample follows PD:
x<-rPD(100,10)
is.PD(x, 100)

##Test whether a very atypical sample where frequencies of different values
## are similar:

x<-c(rep(1, 200), rep(2, 200), rep(3, 200), rep(4, 200), rep(5,200))
is.PD(x,50)