org.ojalgo.random

Class RandomUtils

java.lang.Object

org.ojalgo.random.RandomUtils

Deprecated.

v48

@Deprecated
public abstract class RandomUtils
extends Object

RandomUtils

Author:

apete

Method Summary

Modifier and Type	Method and Description
static double	calculateVariance(double sumOfValues, double sumOfSquaredValues, int numberOfValues) Deprecated. v48 Use SampleSet.calculateVariance(double,double,int) instead
static double	erf(double arg) Deprecated. v48 Use ErrorFunction.erf(double) instead
static double	erfc(double anArg) Deprecated. v48 Use ErrorFunction.erfc(double) instead
static double	erfi(double arg) Deprecated. v48 Use ErrorFunction.erfi(double) instead
static double	factorial(int aVal) Deprecated. v48 Use CombinatorialFunctions.factorial(int) instead
static double	gamma(double arg) Deprecated. v48 Use GammaFunction.gamma(double) instead
static int	partitions(int n, int[] k) Deprecated. v48 Use CombinatorialFunctions.partitions(int,int[]) instead
static int	permutations(int n) Deprecated. v48 Use CombinatorialFunctions.permutations(int) instead
static int	subsets(int n, int k) Deprecated. v48 Use CombinatorialFunctions.subsets(int,int) instead
static int	variations(int n, int k) Deprecated. v48 Use CombinatorialFunctions.variations(int,int) instead

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

calculateVariance

@Deprecated
public static double calculateVariance(double sumOfValues,
                                                   double sumOfSquaredValues,
                                                   int numberOfValues)

Deprecated. v48 Use SampleSet.calculateVariance(double,double,int) instead

Parameters:

sumOfValues - The sum of all values in a sample set

sumOfSquaredValues - The sum of all squared values, in a sample set

numberOfValues - The number of values in the sample set

Returns:

The sample set's variance

erf

@Deprecated
public static double erf(double arg)

Deprecated. v48 Use ErrorFunction.erf(double) instead

Error Function
erf() @ Wikipedia
erf() @ Wolfram MathWorld

erfc

@Deprecated
public static double erfc(double anArg)

Deprecated. v48 Use ErrorFunction.erfc(double) instead

Complementary Error Function
erf() @ Wikipedia
erf() @ Wolfram MathWorld

erfi

@Deprecated
public static double erfi(double arg)

Deprecated. v48 Use ErrorFunction.erfi(double) instead

Inverse Error Function
erf() @ Wikipedia
erf() @ Wolfram MathWorld

factorial

@Deprecated
public static double factorial(int aVal)

Deprecated. v48 Use CombinatorialFunctions.factorial(int) instead

gamma

@Deprecated
public static double gamma(double arg)

Deprecated. v48 Use GammaFunction.gamma(double) instead

Lanczos approximation. The abritray constant is 7, and there are 9 coefficients used. Essentially the algorithm is taken from WikipediA , but it's modified a bit and I found more exact coefficients somewhere else.

partitions

@Deprecated
public static int partitions(int n,
                                         int[] k)

Deprecated. v48 Use CombinatorialFunctions.partitions(int,int[]) instead

Parameters:

n - The number of elements in the set

k - A vector of subset sizes the sum of which must equal the size of the full set

Returns:

The number of ways the set can be partioned in to subsets of the given sizes

permutations

@Deprecated
public static int permutations(int n)

Deprecated. v48 Use CombinatorialFunctions.permutations(int) instead

Parameters:

n - The number of elements in the set

Returns:

The number of permutations of the set

subsets

@Deprecated
public static int subsets(int n,
                                      int k)

Deprecated. v48 Use CombinatorialFunctions.subsets(int,int) instead

Parameters:

n - The number of elements in the set

k - The number of elements in the subset

Returns:

The number of subsets to the set

variations

@Deprecated
public static int variations(int n,
                                         int k)

Deprecated. v48 Use CombinatorialFunctions.variations(int,int) instead

Parameters:

n - The number of elements in the set

k - The size of the tuple

Returns:

The number of ordered k-tuples (variations) of the set