Type: | Package |
Title: | Anderson-Darling GoF test |
Version: | 0.3 |
Date: | 2011-12-28 |
Author: | Carlos J. Gil Bellosta |
Maintainer: | Carlos J. Gil Bellosta <cgb@datanalytics.com> |
Description: | Anderson-Darling GoF test with p-value calculation based on Marsaglia's 2004 paper "Evaluating the Anderson-Darling Distribution" |
License: | GPL-2 | GPL-3 [expanded from: GPL] |
LazyLoad: | yes |
Packaged: | 2011-12-28 01:41:10 UTC; carlos |
Repository: | CRAN |
Date/Publication: | 2011-12-28 13:50:19 |
NeedsCompilation: | no |
Implementation of the Anderson-Darling goodness of fit test.
Description
Implementation of the Anderson-Darling goodness of fit test.
Details
Package: | ADGofTest |
Type: | Package |
Version: | 0.1 |
Date: | 2009-06-26 |
License: | GPL |
LazyLoad: | yes |
Author(s)
Carlos J. Gil Bellosta
Maintainer: Carlos J. Gil Bellosta <cjgb@datanalytics.com>
References
G. and J. Marsaglia, "Evaluating the Anderson-Darling Distribution", Journal of Statistical Software, 2004
Anderson-Darling GoF test
Description
Implementation of the Anderson-Darling goodness of fit test.
Usage
ad.test(x, distr.fun, ...)
Arguments
x |
a random sample from a possibly unknown continuous distribution |
distr.fun |
a named CDF, such as |
... |
extra parameters for the distribution function above, such as location and scale parameters, etc. |
Details
If the distr.fun
is provided, the function checks whether x
is a iid sample from the distribution described by such CDF.
Otherwise, whether they follow a uniform law.
Value
The output is an object of the class htest
exactly like for the Kolmogorov-Smirnov test, ks.test
.
The statistic
and p.value
fields are the most relevant ones.
Author(s)
Carlos J. Gil Bellosta
References
G. and J. Marsaglia, "Evaluating the Anderson-Darling Distribution", Journal of Statistical Software, 2004
Examples
set.seed( 123 )
x <- runif( 100 )
ad.test( x )$p.value
ad.test( x, pnorm, 0, 1 )$p.value
replicate( ad.test( rnorm( 100 ), pnorm )$p.value, 100 )