| Title: | Simultaneous Goodness-of-Fits Tests |
| Version: | 1.0.2 |
| Description: | Routine that allows the user to run several goodness-of-fit tests. It also combines the tests and returns a properly adjusted family-wise p value. Details can be found in <doi:10.48550/arXiv.2007.04727>. |
| Depends: | R (≥ 3.1.0) |
| Imports: | ddst, stats, graphics |
| License: | GPL-2 |
| Encoding: | UTF-8 |
| NeedsCompilation: | no |
| LazyData: | true |
| RoxygenNote: | 7.1.1 |
| Packaged: | 2021-01-23 18:21:35 UTC; Wolfgang |
| Author: | Wolfgang Rolke 
[aut, cre] |
| Maintainer: | Wolfgang Rolke <wolfgang.rolke@upr.edu> |
| Repository: | CRAN |
| Date/Publication: | 2021-01-27 09:00:02 UTC |
TS
Description
This function finds various gof statistics
Usage
TS(x, case)
Arguments
x |
data |
case |
setup info |
Value
A numeric vector with the values of various test statistics.
Examples
case <- list(B=1000, param = NULL, n = 1000, pnull = function(x, param)
punif(x), rnull = function(n, param) runif(n), qnull = function(x, param)
qunif(x), est.mle = function(x) NA, nbins = 10)
case$methods=c("KS", "AD", "CdM", "W", "ZA", "ZK", "ZC")
x <- runif(1000)
TS(x, case)
chisquare.test
Description
This function does the chisquare test
Usage
chisquare.test(x, case, which = "RGd")
Arguments
x |
data set |
case |
setup info |
which |
type of binning (either RGd, Equal Size or Equal Prob) |
Value
A numeric vector of length 1 with the value of the chi-square statistic.
Examples
case <- list(B=1000, param = NULL, n = 1000, pnull = function(x, param) punif(x),
rnull = function(n, param) runif(n), qnull = function(x, param) qunif(x),
est.mle = function(x) NA, nbins = 10)
x <- runif(1000)
chisquare.test(x, case)
simgof.test
Description
This function performs a number of gof tests and rejects the null if any of the tests does so. Then it finds the adjusted p-value.
Usage
simgof.test(
x,
pnull,
rnull,
qnull = function(x) NULL,
do.estimation = TRUE,
estimate = function(x) NULL,
include.methods = c(rep(TRUE, 7), rep(FALSE, 9)),
B = 10000,
lambda,
nbins = NULL
)
Arguments
x |
data set |
pnull |
distribution function under the null hypothesis |
rnull |
routine to generate data under the null hypothesis |
qnull |
quantile function under the null hypothesis |
do.estimation |
TRUE if parameters are to be estimated |
estimate |
routine for parameter estimation |
include.methods |
which methods should be used, a vector of length 16 of T/F |
B |
=10000 number of simulation runs |
lambda |
rate of Poisson if sample size is random |
nbins |
number of bins for chisquare test |
Value
A numeric vector of p values
Examples
x <- runif(1000)
pnull <- function(x) x
rnull <- function(n) runif(n)
qnull <- function(x) x
simgof.test(x, pnull, rnull, qnull, FALSE, B=500)
x <- rnorm(1000, 100, 20)
pnull <- function(x, param) pnorm(x, param[1], param[2])
rnull <- function(n, param) rnorm(x, param[1], param[2])
qnull <- function(x, param) qnorm(x, param[1], param[2])
estimate <- function(x) c(mean(x), sd(x))
simgof.test(x, pnull, rnull, qnull, TRUE, estimate, B=500)
spreadout
Description
This function unbins data. If qnull is given it uses quantiles, otherwise uniform
Usage
spreadout(x, case)
Arguments
x |
data set |
case |
setup info |
Value
A numeric vector of observations without ties.
Examples
case <- list(B=1000, param = NULL, n = 1000, pnull = function(x, param) punif(x),
rnull = function(n, param) runif(n), qnull = function(x, param) qunif(x),
est.mle = function(x) NA, nbins = 10)
y=runif(1000)
bins=seq(0, 1, length=11)
counts=hist(y, bins, plot=FALSE)$counts
x=list(bins=bins,counts=counts)
spreadout(x, case)