Chi.approx: Pearson's three-moment Chi-square approximation
In mlespera/BenGood: Assessing Goodness-of-Fit of Data to Benford's Law
Description
Usage
Arguments
Details
References
See Also
Description
Chi.approx computes upper tail probabilities of asymptotic
distributions for the CVM type statistics using the Pearson chi-square
approximation.
Usage
1
Chi.approx(x, eigvals)
Arguments
x
MLDEFINITION
eigvals
MLDEFINITION
Details
The Chi-square approximation only requires the first three cumulants of the
statistic of interest, and is therefore faster than using the Imhof method.
See Lesperance et. al for further details.
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
mlespera/BenGood documentation built on May 18, 2019, 3:43 p.m.
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Description Usage Arguments Details References See Also
Description
Chi.approx computes upper tail probabilities of asymptotic
distributions for the CVM type statistics using the Pearson chi-square
approximation.
Usage
1 | Chi.approx(x, eigvals)
|
Arguments
x |
MLDEFINITION |
eigvals |
MLDEFINITION |
Details
The Chi-square approximation only requires the first three cumulants of the statistic of interest, and is therefore faster than using the Imhof method. See Lesperance et. al for further details.
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
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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