Class LinearFit
- java.lang.Object
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- dev.nm.stat.evt.evd.univariate.fitting.acer.LinearFit
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public class LinearFit extends Object
Find the parameters for the ACER function from the given empirical epsilon, using OLS regression on the logarithm of the values. That is, \[ \log(\epsilon_k) = \log(q) - a (\eta - b)^c \] Note that there are four variables in the equation, namely, q, b, a, c. This algorithm fixes the value of b and c:- b: the minimum barrier levels, and at most the mean of the observed peaks
- c: 2, or any user-specified value
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description ACERFunction.ACERParameter
fit(double[] eta, double[] epsilon, double peakMean)
Fit the ACER function with OLS.
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Method Detail
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fit
public ACERFunction.ACERParameter fit(double[] eta, double[] epsilon, double peakMean)
Fit the ACER function with OLS. Note: the input epsilon values must be positive (as they represent probabilities).- Parameters:
eta
- the barrier levelsepsilon
- the empirical epsilon valuespeakMean
- the mean of the observed peaks- Returns:
- the fitted ACER parameter
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