Blon.val.sd

A positive integer, which characterizes the data. All (or most) of the data are greater than this "lower bound".

lwbound

A positive integer, which characterizes the data. All (or most) of the data are lower than this "upper bound".

upbound

The chosen position of the digit (from the left).

The function returns the Blondeau Da Silva's standard deviation of the frequency of a digit at a given position (once the associated lower and upper bounds have been specified).

Allows to compare the goodness of fit of Benford's and Blondeau Da Silva's digit distributions in a dataset. It is used to check whether the data distribution is consistent with theoretical distributions highlighted by Blondeau Da Silva or not (through the dat.distr() function): this ideal theoretical distribution must be at least approximately followed by the data for the use of Blondeau Da Silva's model to be well-founded. It also enables to plot histograms of digit distributions, both observed in the dataset and given by the two theoretical approaches (with the digit.ditr() function). Finally, it proposes to quantify the goodness of fit via Pearson's chi-squared test (with the chi2() function).

Blon.val.sd: Blondeau Da Silva's standard deviations

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