SimultBenp: Compare Simultaneous Confidence Intervals against Benford

In mlespera/BenGood: Assessing Goodness-of-Fit of Data to Benford's Law

Description

SimultBenp indicates whether the simultaneous confidence intervals (generated by the user's significant digit frequencies in SimultConf) cover the Benford probabilities.

Usage

SimultBenp(freq, alpha = 0.05, digits = 1:9)

Arguments

freq	Vector of multinomial frequencies.
alpha	Choose alpha to generate (1-α) unspecified, default is 0.05.
digits	A significant digits vector which must match the frequecies freq. If unspecified, default is 1:9. #' @examples set.seed(123) SimultConf((firstdigitsfreq(rnorm(100), 1)), alpha=.05) SimultBenp((firstdigitsfreq(rnorm(100), 1)), alpha=.05)

Value

The output is a vector containing 0's and 1's, where each 0 or 1 corresponds to one of the seven simultaneous confidence intervals (Quesenberry and Hurst, Goodman, etc.). A zero indicates that at least Benford probability falls outside a given CI. A one indicates that all Benford probabilities fall within a given CI.

References

Lesperance M, Reed WJ, Stephens MA, Tsao C, Wilton B (2016) Assessing conformance with Benford's Law: goodness-of-fit tests and simultaneous confidence intervals. PLoS one; 11(3). Wong, S. (2010) Testing Benford's Law with the first two significant digits. University of Victoria, Master's thesis.

See Also

SimultConf

mlespera/BenGood documentation built on May 18, 2019, 3:43 p.m.