Description Usage Arguments Details Value Author(s) References Examples
View source: R/hollander.exp.test.R
Performs Hollander-Proshan test for the composite hypothesis of exponentiality, see Hollander and Proshan (1972).
1 | hollander.exp.test(x, simulate.p.value=FALSE, nrepl=2000)
|
x |
a numeric vector of data values. |
simulate.p.value |
a logical value indicating whether to compute p-values by Monte Carlo simulation. |
nrepl |
the number of replications in Monte Carlo simulation. |
The test is based on the following statistic:
J_n = \frac{1}{n(n - 1)(n - 2)}\, ∑_{i\ne j,k; j<k}1\{x_i > x_j+x_k\}.
Under exponentiality, one has
√{n}(J_n-\frac{1}{4})\stackrel{d}{\rightarrow}\mathcal N≤ft(0,frac{5}{432}\right).
(see Hollander and Proshan (1972)).
A list with class "htest" containing the following components:
statistic |
the value of the test statistic. |
p.value |
the p-value for the test. |
method |
the character string "Hollander-Proshan test for exponentiality". |
data.name |
a character string giving the name(s) of the data. |
Alexey Novikov and Ruslan Pusev
Hollander M., Proshan F. (1972): Testing whether new is better than used. — Ann. Math. Stat., vol. 43, pp. 1136–1146.
1 2 | hollander.exp.test(rexp(25))
hollander.exp.test(rgamma(25,2))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.