is.PD {PEkit} | R Documentation |
Test for the shape of the distribution
Description
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.
Usage
is.PD(x, rounds)
Arguments
x |
A discrete data vector. |
rounds |
How many samples are simulated to obtain the empirical distribution. |
Details
The calculated test statistic is
W=\sum_{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 \psi
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 \psi
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.
Value
A p-value.
References
Watterson, G.A., (1978), The homozygosity test of neutrality. Genetics. 88(2):405-417.
Examples
##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)