Rgof (version 3.2.0)

gof_test_adjusted_pvalue: This function performs a number of gof tests and finds the adjusted p value for the combined test

Description

This function performs a number of gof tests and finds the adjusted p value for the combined test

Usage

gof_test_adjusted_pvalue(
  x,
  vals = NA,
  pnull,
  rnull,
  w = function(x) -99,
  phat = function(x) -99,
  TS,
  TSextra = NA,
  nbins = c(50, 10),
  rate = 0,
  Range = c(-Inf, Inf),
  B = c(5000, 1000),
  minexpcount = 5,
  ChiUsePhat = TRUE,
  maxProcessor,
  doMethods
)

Value

None

Arguments

x

data set

vals

=NA, values of discrete RV, or NA if data is continuous

pnull

cdf under the null hypothesis

rnull

routine to generate data under the null hypothesis

w

(Optional) function to calculate weights, returns -99 if no weights

phat

=function(x) -99, function to estimate parameters from the data, or -99 if no parameters are estimated

TS

user supplied function to find test statistics, if any

TSextra

=NA, list passed to TS, if desired, or NA

nbins

=c(100, 10) number of bins for chi-square tests

rate

=0 rate of Poisson if sample size is random, 0 if sample size is fixed

Range

=c(-Inf, Inf) limits of possible observations, if any, for chi-square tests

B

=c(5000,1000) number of simulation runs for individual and for adjusted p values

minexpcount

=5 minimal expected bin count required

ChiUsePhat

= TRUE, if TRUE param is estimated parameter, otherwise minimum chi square method is used.

maxProcessor

number of cores to use

doMethods

Methods to include in tests

Examples

# Tests to see whether data comes from a standard normal distribution.
pnull = function(x) pnorm(x)
rnull = function()  rnorm(100)
x = rnorm(100)
gof_test_adjusted_pvalue(x, NA, pnull, rnull, B=c(500, 200), 
                            maxProcessor=1)
# Tests to see whether data comes from a normal distribution with standard deviation 1 
# and the mean estimated.
pnull=function(x, m) pnorm(x, m)
rnull=function(m) rnorm(100, m)
TSextra = list(qnull=function(x, m=0) qnorm(x, m))
phat=function(x) mean(x)
x = rnorm(100, 1, 2)
gof_test_adjusted_pvalue(x, NA, pnull, rnull, phat=phat, 
                        TSextra=TSextra, B=c(500, 200), maxProcessor=1)
# Tests to see whether data comes from a binomial (10, 0.5) distribution.
vals=0:10
pnull = function() pbinom(0:10, 10, 0.5)
rnull = function() table(c(0:10, rbinom(1000, 10, 0.5)))-1
x = rnull() 
gof_test_adjusted_pvalue(x, vals, pnull, rnull, 
                        B=c(500, 200), maxProcessor=1)
# Tests to see whether data comes from a binomial distribution with 
# the success probability estimated from the data.
pnull = function(p=0.5) pbinom(0:10, 10, p)
rnull = function(p=0.5) table(c(0:10, rbinom(1000, 10, p)))-1
phat=function(x) mean(rep(0:10,x))/10 
gof_test_adjusted_pvalue(x, vals, pnull, rnull, phat=phat, 
                        B=c(500, 200), maxProcessor=1)