Probabilities::BinomPDF Function

Overload List

#	Signature	Description
1	double BinomPDF(int x, int N, double p);	Binomial probability mass function (PMF).
2	void BinomPDF(TMtxVecInt X, int* n, double P, TDenseMtxVec *Res);	Binomial PDF (vectorized).

Binomial probability mass function (PMF).

#	Name	Type	Description
1	x	int	Function domain, integer on the closed interval [0,N].
2	N	int	Number of trials; N must be a positive integer.
3	p	double	Success probability; p must lie on the closed interval [0,1].

Returns: the binomial probability mass function (PMF). Returns NAN when p is outside [0,1], N<=0, or x>N.

Remarks:

Computes the binomial PMF, the probability of observing exactly x successes in N independent Bernoulli trials each with success probability p:

PMF(x| N,p)=binomNx p^x (1-p)^(N-x), x=0,1,...,N

Domain: x in {0,1,...,N}, N >= 1, p in [0,1]. For p not in [0,1], N <= 0 or x>N the result is NaN.

To recognize a situation that involves a binomial random variable, the following assumptions must be met:

The experiment consists of a fixed number, N, of Bernoulli trials that result in either success or failure.
The trials are identical and independent, so the success probability p remains the same from trial to trial.
The random variable x denotes the number of successes obtained in the N trials.

Declared in Dew::Math::Units::Probabilities · Dew.Math/Units.Probabilities.h · Cross-compiler

Binomial PDF (vectorized).

#	Name	Type	Description
1	X	TMtxVecInt *	Defines distribution domain, real vector or matrix with integer values on closec interval [0,n].
2	n	int	Defines number of trials. n must be a positive integer.
3	P	double	Defines success probability. p must lie on the [0,1] closed interval.
4	Res	TDenseMtxVec *	After calculation stores the PDF calculated using X, n and p. Length and Complex properties of Res are adjusted automatically to match Length and Complex properties of X.

Declared in Dew::Math::Units::Probabilities · Dew.Math/Units.Probabilities.h · Cross-compiler