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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 | CDF | Quantile | |
---|---|---|---|
Univariate Discrete Distribution | discrete_pdf | discrete_cdf | discrete_inv |
Empirical Distribution | empirical_pdf | empirical_cdf | empirical_inv |
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.
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.
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.
For each element of x, compute the probability density function (PDF) at x of the empirical distribution obtained from the univariate sample data.
For each element of x, compute the cumulative distribution function (CDF) at x of the empirical distribution obtained from the univariate sample 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.
Next: Random Number Generation, Previous: Correlation and Regression Analysis, Up: Statistics [Contents][Index]