Namespaces

Types in MathNet.Numerics.Distributions

Type Multinomial

Namespace MathNet.Numerics.Distributions

Interfaces IDistribution

Multivariate Multinomial distribution. For details about this distribution, see.
The distribution is parameterized by a vector of ratios: in other words, the parameter does not have to be normalized and sum to 1. The reason is that some vectors can't be exactly normalized to sum to 1 in floating point representation.

Constructors

Static Functions

Methods

Properties

Public Constructors

Multinomial(Double[] p, int n)

Initializes a new instance of the Multinomial class.
Parameters
Double[] p

An array of nonnegative ratios: this array does not need to be normalized as this is often impossible using floating point arithmetic.

int n

The number of trials.

Multinomial(Double[] p, int n, Random randomSource)

Initializes a new instance of the Multinomial class.
Parameters
Double[] p

An array of nonnegative ratios: this array does not need to be normalized as this is often impossible using floating point arithmetic.

int n

The number of trials.

Random randomSource

The random number generator which is used to draw random samples.

Multinomial(Histogram h, int n)

Initializes a new instance of the Multinomial class from histogram h. The distribution will not be automatically updated when the histogram changes.
Parameters
Histogram h

Histogram instance

int n

The number of trials.

Public Static Functions

bool IsValidParameterSet(IEnumerable<double> p, int n)

Tests whether the provided values are valid parameters for this distribution.
Parameters
IEnumerable<double> p

An array of nonnegative ratios: this array does not need to be normalized as this is often impossible using floating point arithmetic.

int n

The number of trials.

Return
bool

If any of the probabilities are negative returns false , if the sum of parameters is 0.0, or if the number of trials is negative; otherwise true.

Int32[] Sample(Random rnd, Double[] p, int n)

Samples one multinomial distributed random variable.
Parameters
Random rnd

The random number generator to use.

Double[] p

An array of nonnegative ratios: this array does not need to be normalized as this is often impossible using floating point arithmetic.

int n

The number of trials.

Return
Int32[]

the counts for each of the different possible values.

IEnumerable<Int32[]> Samples(Random rnd, Double[] p, int n)

Samples a multinomially distributed random variable.
Parameters
Random rnd

The random number generator to use.

Double[] p

An array of nonnegative ratios: this array does not need to be normalized as this is often impossible using floating point arithmetic.

int n

The number of variables needed.

Return
IEnumerable<Int32[]>

a sequence of counts for each of the different possible values.

Public Methods

bool Equals(object obj)

int GetHashCode()

Type GetType()

double Probability(Int32[] x)

Computes values of the probability mass function.
Parameters
Int32[] x

Non-negative integers x1,..., xk

Return
double

The probability mass at location x.

double ProbabilityLn(Int32[] x)

Computes values of the log probability mass function.
Parameters
Int32[] x

Non-negative integers x1,..., xk

Return
double

The log probability mass at location x.

Int32[] Sample()

Samples one multinomial distributed random variable.
Return
Int32[]

the counts for each of the different possible values.

IEnumerable<Int32[]> Samples()

Samples a sequence multinomially distributed random variables.
Return
IEnumerable<Int32[]>

a sequence of counts for each of the different possible values.

string ToString()

A string representation of the distribution.
Return
string

a string representation of the distribution.

Public Properties

Vector<T> Mean get;

Gets the mean of the distribution.

int N get;

Gets the number of trials.

Double[] P get;

Gets the proportion of ratios.

Random RandomSource get; set;

Gets or sets the random number generator which is used to draw random samples.

Vector<T> Skewness get;

Gets the skewness of the distribution.

Vector<T> Variance get;

Gets the variance of the distribution.