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26.5 Distributions

Octave has functions for computing the Probability Density Function (PDF), the Cumulative Distribution function (CDF), and the quantile (the inverse of the CDF) for arbitrary user-defined distributions (discrete) and for experimental data (empirical).

The following table summarizes the supported distributions (in alphabetical order).

Distribution	PDF	CDF	Quantile
Univariate Discrete Distribution	discrete_pdf	discrete_cdf	discrete_inv
Empirical Distribution	empirical_pdf	empirical_cdf	empirical_inv

: pdf = discrete_pdf (x, v, p) ¶

For each element of x, compute the probability density function (PDF) at x of a univariate discrete distribution which assumes the values in v with probabilities p.

: cdf = discrete_cdf (x, v, p) ¶

For each element of x, compute the cumulative distribution function (CDF) at x of a univariate discrete distribution which assumes the values in v with probabilities p.

: q = discrete_inv (x, v, p) ¶

For each element of x, compute the quantile (the inverse of the CDF) at x of the univariate distribution which assumes the values in v with probabilities p.

: pdf = empirical_pdf (x, data) ¶

For each element of x, compute the probability density function (PDF) at x of the empirical distribution obtained from the univariate sample data.

: cdf = empirical_cdf (x, data) ¶

For each element of x, compute the cumulative distribution function (CDF) at x of the empirical distribution obtained from the univariate sample data.

: q = empirical_inv (x, data) ¶

For each element of x, compute the quantile (the inverse of the CDF) at x of the empirical distribution obtained from the univariate sample data.