Description Usage Arguments Details Value Author(s) References Examples
Performs the empirical distribution function goodness-of-fit test of Poisson distribution with unknown parameter
1 | testdelta2(x, n.boot)
|
x |
vector of nonnegative integers, the sample data |
n.boot |
number of bootstrap replicates |
The test of Poissonity Δ_{2} was proposed by Puig and Weibb (2020). The test is based on some characterizations like the Binomial thinning operator for the probability generating function of a Poisson distribution. The test statistic is based on the L2 norm.
\hat{Δ}_2=\int_{0}^{1} (\hat{g}(t) - [\hat{g}(t)(\frac{t+1}{2})]^2) ^2 dt
\hat{g}(t) denotes the empirical pobability generating function of X.
The test is implemented by parametric boostrap with n.boot
replicates
The function testDelta2
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 |
Manuel Mendez Hurtado mmendezinformatica@gmail.com
Puig, P and Weibb, C. H. (2020) Empirical-distribution-function goodness-of-fit tests for discrete models, Computational Statistics and Data Analysis Vol 144, 1-12 https://www.sciencedirect.com/science/article/pii/S0167947319302336
1 2 | x <- rpois(20,2)
testdelta2(x, n.boot = 500)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.