Reference guides are available for functions and commands supported by OML, Tcl, and Python.
The Reference Guide contains documentation for all functions supported in the OpenMatrix language.
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OpenMatrix is a mathematical scripting language.
Generates a design matrix for Box-Behnken with specified number of factors f.
Beta function.
Compute beta distribution cumulative distribution function values.
Fit a beta distribution to a data sample.
Compute incomplete beta function values.
Compute beta distribution inverse cumulative distribution function values.
Log beta function.
Compute beta distribution probability density function values.
Generate random data from a beta distribution.
Divides the range of data d into n equal bins.
Compute cumulative distribution function values.
Compute chi-squared distribution cumulative distribution function values.
Compute chi-squared distribution inverse cumulative distribution function values.
Compute chi-squared distribution probability density function values.
Generate random data from a chi-squared distribution.
Compute correlation coefficients.
Compute covariances.
Compute cross spectral densities.
Removes the mean or best fit line from a data vector.
Returns the error function of x.
Compute exponential distribution cumulative distribution function values.
Fit an exponential distribution to a data sample.
Compute exponential distribution inverse cumulative distribution function values.
Compute exponential distribution probability density function values.
Generate random data from an exponential distribution.
Factorial function.
Compute F distribution cumulative distribution function values.
Compute F distribution inverse cumulative distribution function values.
Compute F distribution probability density function values.
Generate random data from an F distribution.
Generate the full factorial design matrices.
Compute gamma distribution cumulative distribution function values.
Fit a gamma distribution to a data sample.
Compute gamma distribution inverse cumulative distribution function values.
Gamma function.
Log gamma function.
Compute incomplete gamma function values.
Compute gamma distribution probability density function values.
Generate random data from a gamma distribution.
Compute inverse cumulative distribution function values.
Compute kurtosis values.
Compute lognormal distribution cumulative distribution function values.
Fit a lognormal distribution to a data sample.
Compute lognormal distribution inverse cumulative distribution function values.
Compute lognormal distribution probability density function values.
Generate random data from a normal distribution.
Compute mean or median absolute deviation values.
Computes mean values.
Compute mean absolute deviation values.
Compute median values.
Compute mode values.
Combinatorial function for selecting from a set of items.
Compute normal distribution cumulative distribution function values.
Fit a normal distribution to a data sample.
Compute normal distribution inverse cumulative distribution function values.
Compute normal distribution probability density function values.
Compute probability density function values.
Compute Poisson distribution cumulative distribution function values.
Fit a Poisson distribution to a data sample.
Compute Poisson distribution inverse cumulative distribution function values.
Compute Poisson distribution probability density function values.
Generate random data from a Poisson distribution.
Fit a polynomial to a set of paired data.
Generate uniform random values on the interval (0,1).
Generate standard normal random values.
Generate random samples from a distribution.
Generates a random permutation vector.
Perform multiple linear regression using the model y = X * beta + e.
Compute root mean square values.
Compute skewness values.
Returns the standard deviation of x.
Compute Student t distribution cumulative distribution function values.
Compute Student t distribution inverse cumulative distribution function values.
Compute Student t distribution probability density function values.
Generate random data from a Student t distribution.
Hypothesis test for the mean of a sample with unknown standard deviation.
Hypothesis test for the means of two samples with unknown and equal standard deviations.
Compute uniform distribution cumulative distribution function values.
Compute uniform distribution inverse cumulative distribution function values.
Fit a uniform distribution to a data sample.
Compute uniform distribution probability density function values.
Generate random data from a uniform distribution.
Compute variance values.
Hypothesis test for the variance of a sample.
Hypothesis test for the variances of two samples.
Compute Weibull distribution cumulative distribution function values.
Fits a Weibull distribution to a data sample.
Compute Weibull distribution inverse cumulative distribution function values.
Compute Weibull distribution probability density function values.
Generate random data from a Weibull distribution.
Hypothesis test for the mean of a sample with known standard deviation.