51 lines
1.2 KiB
Java
51 lines
1.2 KiB
Java
|
package statistics;
|
||
|
|
|
||
|
|
public class GaussianWrapper {
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Returns standard Gaussian cdf approximation based on algortihm for error function.
|
||
|
|
*
|
||
|
|
* @param value Value
|
||
|
|
* @return Probability
|
||
|
|
*/
|
||
|
|
public static double cdfErrorAlgo(double value) {
|
||
|
|
return CDF_Normal.normp(value);
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Returns Gaussian cdf approximation based on algorithm for error function.
|
||
|
|
*
|
||
|
|
* @param value Value
|
||
|
|
* @param mean Mean value
|
||
|
|
* @param stdDev Standard deviance
|
||
|
|
* @return Probability
|
||
|
|
*/
|
||
|
|
public static double cdfErrorAlgo(double value, double mean, double stdDev) {
|
||
|
|
return CDF_Normal.normp((value - mean) / stdDev);
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Returns standard Gaussian cdf using Taylor approximation.
|
||
|
|
*
|
||
|
|
* @param value Value
|
||
|
|
* @return Probability
|
||
|
|
*/
|
||
|
|
public static double cdfTaylor(double value) {
|
||
|
|
return Gaussian.Phi(value);
|
||
|
|
}
|
||
|
|
|
||
|
|
/**
|
||
|
|
* Returns Gaussian cdf using Taylor approximation .
|
||
|
|
*
|
||
|
|
* @param value Value
|
||
|
|
* @param mean Mean value
|
||
|
|
* @param stdDev Standard deviance
|
||
|
|
* @return Probability
|
||
|
|
*/
|
||
|
|
public static double cdfTaylor(double value, double mean, double stdDev) {
|
||
|
|
return Gaussian.Phi(value, mean, stdDev);
|
||
|
|
}
|
||
|
|
|
||
|
|
}
|
||
|
|
|