erf
Returns the error function of x.
Syntax
erf(x)
Inputs
- x
- Any scalar or real matrix.
Outputs
- R
Example
Simple erf example:
erf([0.3, -0.01, 1.1;-0.3, 1, 2])
R = [ 0.328627 -0.0112834 0.880205 ; -0.328627 0.842701 0.995322 ]
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Beta function.
Compute beta distribution cumulative distribution function values.
Fit a beta distribution to a data sample.
Compute beta distribution inverse cumulative distribution function values.
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.
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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.
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Removes the mean or best fit line from a data vector.
Returns the error function of x.
Compute exponential distribution cumulative distribution function values.
Fits an exponential curve to data using a log transformation to create a linear model.
Fit an exponential distribution to a data sample.
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Generate random data from an exponential distribution.
Factorial function.
Compute F distribution cumulative distribution function values.
Compute F distribution inverse cumulative distribution function values.
Returns the mean, variance, skewness and kurtosis of the sample x.
Compute F distribution probability density function values.
Generate random data from an F distribution.
Generate the full factorial design matrices.
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Fit a gamma distribution to a data sample.
Compute gamma distribution inverse cumulative distribution function values.
Gamma function.
Compute gamma distribution probability density function values.
Generate random data from a gamma distribution.
Returns the geometric mean of x.
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.
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Compute mean absolute deviation values.
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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.
Generate random data from a normal distribution.
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.
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Compute skewness values.
Returns the standard deviation of x.
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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.
Returns the uniform distribution parameters of x
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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.
Describes all of the blocks in the installed Activate library.
Key terms associated with the software.
Define shortcuts to common operations.
Explore the Extended Definitions, OML Guides, Block Library, API Guide and Glossary.
The Reference Guide contains documentation for all functions supported in the OpenMatrix language.
Returns the error function of x.
Returns the error function of x.
erf(x)
Simple erf example:
erf([0.3, -0.01, 1.1;-0.3, 1, 2])
R = [ 0.328627 -0.0112834 0.880205 ; -0.328627 0.842701 0.995322 ]
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