digitTests: Tests for Detecting Irregular Data Patterns

digitTests is an R package providing tests for detecting irregular data patterns.

The package and its analyses are also implemented with a graphical user interface in the Audit module of JASP, a free and open-source statistical software program.

Author

Koen Derks (maintainer, author)

<k.derks@nyenrode.nl>

Please use the citation provided by R when citing this package. A BibTex entry is available from citation("digitTests").

See also

Useful links:

• The issue page to submit a bug report or feature request.

Examples

# Load the digitTests package
library(digitTests)

############################################
### Example 1: Benford's Law ####
############################################

data('sinoForest')
distr.test(sinoForest$value, check = 'first', reference = 'benford')
#> 
#> 	Digit distribution test
#> 
#> data:  sinoForest$value
#> n = 772, X-squared = 7.6517, df = 8, p-value = 0.4682
#> alternative hypothesis: leading digit(s) are not distributed according to the benford distribution.

###################################
### Example 2: Repeated Values ####
###################################

data('sanitizer')
rv.test(sanitizer$value, check = 'lasttwo', method = 'af', B = 1000)
#> 
#> 	Repeated values test
#> 
#> data:  sanitizer$value
#> n = 1600, AF = 1.5225, p-value = 0.002
#> alternative hypothesis: average frequency in data is greater than for random data.