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class GoodnessOfFit_KS extends Error

The GoodnessOfFit_KS class is used to fit data to a probability distribution. It uses the Kolmogorov-Smirnov Goodness of Fit Test. Determine the maximum absolute difference 'd_max' between the data points 'd_i' and the theoretical value from a CDF F,

d_max = max 1≤i≤n {|Fe(d_i) - F(d_i)|} (concept)

d_max = max 1≤i≤n {F(d_i) − (i−1)/n, i/n − F(d_i)} (calculation)

where 'Fe(.)' is the empirical distribution and 'F(.)' is the theoretical distribution. If 'd_max' is large, the fit should be rejected.

See also

www.itl.nist.gov/div898/handbook/eda/section3/eda35g.htm ---------------------------------------------------------------------------------

www.eg.bucknell.edu/~xmeng/Course/CS6337/Note/master/node66.html

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  1. new GoodnessOfFit_KS(d: VectorD, makeStandard: Boolean = true)

    d

    the sample data points

    makeStandard

    whether to transform the data to zero mean and unit standard deviation

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  9. def fit(cdf: Distribution, parms: Parameters = null): Double

    Perform a KS goodness of fit test, matching the CDF of the given data 'd' with the random variable's Cumulative Distribution Function (CDF).

    Perform a KS goodness of fit test, matching the CDF of the given data 'd' with the random variable's Cumulative Distribution Function (CDF).

    cdf

    the Cumulative Distribution Function to test

    parms

    the parameters for the distribution

    See also

    www.usna.edu/Users/math/dphillip/sa421.f13/chapter02.pdf

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