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Statistical hypothesis tests based on Matrix data.
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package se.alipsa.groovy.stats.timeseries
import se.alipsa.groovy.matrix.Matrix
/**
* A portmanteau test is a type of statistical hypothesis test in which the null hypothesis is well specified,
* but the alternative hypothesis is more loosely specified.
* Tests constructed in this context can have the property of being at least moderately powerful against a
* wide range of departures from the null hypothesis. Thus, in applied statistics, a portmanteau test
* provides a reasonable way of proceeding as a general check of a model's match to a dataset where there
* are many different ways in which the model may depart from the underlying data generating process.
* Use of such tests avoids having to be very specific about the particular type of departure being tested.
*/
class Portmanteau {
/**
* The Ljung–Box test (named for Greta M. Ljung and George E. P. Box) is a type of statistical test of whether
* any of a group of autocorrelations of a time series are different from zero.
* Instead of testing randomness at each distinct lag, it tests the "overall" randomness based on a number of
* lags, and is therefore a portmanteau test.
*/
Matrix ljungBox(Matrix table) {
return null
}
}