Description Usage Arguments Details Value References Examples
Skewed normal fit for null or transformed null similarity scores.
1 | null.sn.fit(score.null.vec, standardizeQ = FALSE, plotQ = FALSE)
|
score.null.vec |
Vector of null (non-match) similarity scores or transformed similarity scores |
standardizeQ |
Whether or not to standardize the null scores |
plotQ |
Diagnostic plots? |
The skewed normal distribution is a flexible three parameter distribution which often gives
a good fit to the null log similarity scores when these scores are on a scale of 0 to 1. Other than
standardization, this function assumes that if the user wants the scores to be transformed, they've
transformed them. This routine calls the selm
function from the sn package.
list with the fitted parameters, fit info and chi-square goodness of fit test results
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1 | XXXX
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