CVMEigen: Compute eigenvalues required for function CVMStats
In mlespera/BenGood: Assessing Goodness-of-Fit of Data to Benford's Law
Description
Usage
Arguments
Value
References
See Also
Description
CVMEigen computes eigenvalues needed for computation of significance
levels of Cramer-von Mises type statistics for testing H_0: Benford vs
H_1: multinomial p's.
Usage
1
CVMEigen(digits)
Arguments
digits
A significant digits vector.
Value
The output is a list of three component vectors of eigenvalues:
$eig.W as Cramer-von Mises, $eig.U as Watson, and
$eig.A as Anderson-Darling respectively.
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 Value References See Also
Description
CVMEigen computes eigenvalues needed for computation of significance
levels of Cramer-von Mises type statistics for testing H_0: Benford vs
H_1: multinomial p's.
Usage
1 | CVMEigen(digits)
|
Arguments
digits |
A significant digits vector. |
Value
The output is a list of three component vectors of eigenvalues:
$eig.W as Cramer-von Mises, $eig.U as Watson, and
$eig.A as Anderson-Darling respectively.
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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