Uses of Class
com.softnetConsult.utils.math.Distribution

Packages that use Distribution

com.softnetConsult.utils.math

This package contains commonly used mathematical and statistical functions, finctions for bit-map processing and futher mathematical classes.

Uses of Distribution in com.softnetConsult.utils.math

Methods in com.softnetConsult.utils.math that return Distribution

Distribution<java.lang.Double>	Distribution.discretise(double interval) Discretises this sample into intervals of the specified length.
Distribution<java.lang.Integer>	Distribution.discretise(int interval) Discretises this sample into intervals of the specified length.
Distribution<java.lang.Double>	Distribution.discretise(T min, T max, double interval) Discretises this sample into intervals of the specified length while only considering the observations between min and max (inclusive). If S = (max - min) / interval, the resulting distribution will contain S observations if (max - min) is not exactly dividable by interval, otherwise it will contain S + 1 observations. The first observation of the resulting distrinution will be min and the corresponding frequency will be the sum of the frequencies of all observations between min (inclusive) and min + inverval (exclusive) in this original distribution. The n-th observation of the resulting distrinution will be (min + (n-1) * interval and the corresponding frequency will be the sum of the frequencies of all observations between min + (n-1) * inverval (inclusive) and min + n * inverval (exclusive) in this original distribution.
Distribution<java.lang.Integer>	Distribution.discretise(T min, T max, int interval) Discretises this sample into intervals of the specified length while only considering the observations between min and max (inclusive). If S = (max - min) / interval, the resulting distribution will contain S observations if (max - min) is not exactly dividable by interval, otherwise it will contain S + 1 observations. The first observation of the resulting distrinution will be min and the corresponding frequency will be the sum of the frequencies of all observations between min (inclusive) and min + inverval (exclusive) in this original distribution. The n-th observation of the resulting distrinution will be (min + (n-1) * interval and the corresponding frequency will be the sum of the frequencies of all observations between min + (n-1) * inverval (inclusive) and min + n * inverval (exclusive) in this original distribution.
Distribution<T>	Distribution.getLogDistribution(double base) Returns a new Distribution in which each observation frequency equals to the logarithm of the corresponding observation frequency of this distribution; all resulting non-integer frequencies are rounded to the nearest integer.
Distribution<T>	Distribution.normaliseBy(double value) Returns a new Distribution in which each observation frequency equals to the observation frequency of this distribution divided by the specified value; all resulting non-integer frequencies are rounded to the nearest integer.
Distribution<T>	Distribution.selectInterval(T min, T max) A sample that contains only the values of this sample between the specified boundaries.

Methods in com.softnetConsult.utils.math with parameters of type Distribution

static Pair<double[],double[]>

StatsTools.lnTransform(Distribution<? extends java.lang.Number> dist) Computes a linear transform of the specified distribution sample by using the observed values as x-values and observation frequencies as y-values of a data series.