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.eg.bucknell.edu/~xmeng/Course/CS6337/Note/master/node66.html
www.itl.nist.gov/div898/handbook/eda/section3/eda35g.htm ---------------------------------------------------------------------------------
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- 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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- 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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