phitest: Nonparametric goodness-of-fit methods based on phi-divergences
This package perform a generalized goodness-of-fit test
based on phi-divergences. This test works by considering the
maximum 'distance' between the hypothesized distribution
function and the empirical distribution function, where the
measure of 'distance' is based on a phi-divergence. This
generalized family of tests is indexed by a real-valued
parameter, s, wich can take values in [-1,2]. Special cases of
this family include the Berk-Jones statistic (s=0), the
supremum form of the Anderson-Darling statistic (s=2), and the
statistic of Jaescke and Eicker (s=-1). See the references for
the phi.test() function for references regarding these special
cases. In addition to performing a statistical test, this
package will also invert the test statistic to form and plot
confidence bands for the true distribution function for sample
sizes up to 10,000.
| Version: |
1.0-0 |
| Depends: |
R (≥ 2.7.0) |
| Published: |
2010-08-10 |
| Author: |
Leah R. Jager |
| Maintainer: |
Leah R. Jager <jager at usna.edu> |
| License: |
GPL |
| CRAN checks: |
phitest results |
Downloads: