testu: Dispersion Index Test for Poisson Distribution

In MMH1997/TestPoissonity: Goodness-of-fit test for Poisson Distribution.

Description

Performs the disperssion index goodness-of-fit test of Poisson distribution with unknown parameter.

Usage

testu(x, n.boot)

Arguments

x	vector of nonnegative integers, the sample data.
n.boot	number of bootstrap replicates. If n.boot = 0, it uses the normal approximation method.

Details

The test of Poissonity u is based on a normalization of the Disperssion Index, equal to 1 in a Poisson Distribution.

u = (D √{\frac{n - 1}{2(1 - 1/N)}}

D denotes the disperssion index of X.

N denotes the sum of X.

n denotes the length of X.

The test is implemented by parametric boostrap with n.boot replicates or by normal approximation.

Value

The function testu returns a list with class htest containing:

	Description of test.
data	Description of data.
test statistic	Value of test statistic.
p-value	approximate p-value of the test.
mean	sample mean.

Author(s)

Manuel Mendez Hurtado [e-mail]

References

IAEA (2011) Cytogenetic Dosimetry: Applications in Preparedness for and Response to Radiation Emergencies https://www.iaea.org/es/publications/10456/cytogenetic-dosimetry-applications-in-preparedness-for-and-response-to-radiation-emergencies

Rao, C. R., Chakravarti, I.M. (1956) Some small sample test of significance for a Poisson Distribution Biometrics Vol 12, 264-282 https://www.jstor.org/stable/3001466?seq=1

Examples

x <- rpois(20,2)
testu(x, n.boot = 500)
testu(x, n.boot = 0)

MMH1997/TestPoissonity documentation built on Dec. 17, 2021, 2:11 a.m.