Chi-SquaredFit v0.7.6 Chi2fit.Distribution View Source

Provides various distributions.

Link to this section Summary

Functions

The Bernoulli distribution

Distribution for flipping coins

Constant distribution

Distribution simulating a dice (1..6)

Distribution simulating the dice in the GetKanban V4 simulation game

The Erlang distribution

The Erlang cumulative distribution function

The exponential distribution

Calculates the gamma function of its argument up to 8 figures

Returns the model for a name

The normal or Gauss distribution

The normal or Gauss cumulative distribution

The Poisson distribution

The Skew Exponential Power cumulative distribution (Azzalini)

Uniform distribution

Uniform distribution

Wald or Inverse Gauss distribution

The Wald (Inverse Gauss) cumulative distribution function

The Weibull distribution

The Weibull cumulative distribution function

Link to this section Types

Link to this type cdf() View Source
cdf() :: number :: number
Link to this type distribution() View Source
distribution() :: ... :: number

Link to this section Functions

Link to this function bernoulli(value) View Source
bernoulli(value :: number) :: distribution

The Bernoulli distribution.

Distribution for flipping coins.

Link to this function constant(average) View Source
constant(number | Keyword.t) :: distribution

Constant distribution.

Distribution simulating a dice (1..6)

Link to this function dice_gk4(avg) View Source
dice_gk4([] | number) :: distribution

Distribution simulating the dice in the GetKanban V4 simulation game.

Link to this function erlang(k, lambda) View Source
erlang(k :: integer, lambda :: number) :: distribution

The Erlang distribution.

Link to this function erlangCDF(k, lambda) View Source
erlangCDF(k :: number, lambda :: number) :: cdf

The Erlang cumulative distribution function.

The exponential distribution.

Link to this function gamma(x) View Source
gamma(x :: float) :: float

Calculates the gamma function of its argument up to 8 figures

Reference

See Abramowitz & Stegun, Mathematical Handbook of Functions, formula 6.1.36

Link to this function guess(sample, n \\ 100, list \\ ["exponential", "poisson", "normal", "erlang", "wald", "sep", "weibull"]) View Source
guess(sample :: [number], n :: integer, list :: [String.t] | String.t) :: [any]

Guesses what distribution is likely to fit the sample data

Link to this function model(name, options \\ []) View Source
model(name :: String.t, options :: Keyword.t) :: [fun: cdf, df: pos_integer]

Returns the model for a name.

Supported disributions:

"wald" - The Wald or Inverse Gauss distribution,
"weibull" - The Weibull distribution,
"exponential" - The exponential distribution,
"sep" - The Skewed Exponential Power distribution (Azzalini),
"sep0" - The Skewed Exponential Power distribution (Azzalini) with location parameter set to zero (0).

Options

Available only for the SEP distribution, see ‘sepCDF/5’.

Link to this function normal(mean, sigma) View Source
normal(mean :: number, sigma :: number) :: distribution

The normal or Gauss distribution

Link to this function normalCDF(mean, sigma) View Source
normalCDF(mean :: number, sigma :: number) :: cdf

The normal or Gauss cumulative distribution

The Poisson distribution.

Link to this function sepCDF(a, b, lambda, alpha, options \\ []) View Source
sepCDF(a :: float, b :: float, lambda :: float, alpha :: float, options :: Keyword.t) :: cdf

The Skew Exponential Power cumulative distribution (Azzalini).

Options

:method - the integration method to use, :gauss and :romberg types are supported, see below :tolerance - re-iterate until the tolerance is reached (only for :romberg) :points - the number of points to use in :gauss method

Integration methods

:gauss - n-point Gauss rule, :gauss2 - n-point Guass rule with tanh transformation, :gauss3 - n-point Gauss rule with linear transformstion, :romberg - Romberg integration, :romberg2 - Romberg integration with tanh transformation, :romberg3 - Romberg integration with linear transformstion.

Uniform distribution.

Link to this function uniform(min, max) View Source
uniform(min :: integer, max :: integer) :: distribution

Uniform distribution.

Link to this function wald(mu, lambda) View Source
wald(mu :: number, lambda :: number) :: distribution

Wald or Inverse Gauss distribution.

Link to this function waldCDF(mu, lambda) View Source
waldCDF(number, number) :: cdf

The Wald (Inverse Gauss) cumulative distribution function.

Link to this function weibull(alpha, beta) View Source
weibull(number, number | Keyword.t) :: distribution

The Weibull distribution.

Link to this function weibullCDF(k, lambda) View Source
weibullCDF(number, number) :: cdf

The Weibull cumulative distribution function.