Chi-SquaredFit v0.8.0 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
Guesses what distribution is likely to fit the sample data
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 section Functions
The Bernoulli distribution.
Distribution for flipping coins.
constant(number() | Keyword.t()) :: distribution()
Constant distribution.
Distribution simulating a dice (1..6)
Distribution simulating the dice in the GetKanban V4 simulation game.
erlang(k :: integer(), lambda :: number()) :: distribution()
The Erlang distribution.
The Erlang cumulative distribution function.
The exponential distribution.
Calculates the gamma function of its argument up to 8 figures
Reference
See Abramowitz & Stegun, Mathematical Handbook of Functions, formula 6.1.36
Guesses what distribution is likely to fit the sample data
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’.
normal(mean :: number(), sigma :: number()) :: distribution()
The normal or Gauss distribution
The normal or Gauss cumulative distribution
The Poisson distribution.
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.
uniform(min :: integer(), max :: integer()) :: distribution()
Uniform distribution.
wald(mu :: number(), lambda :: number()) :: distribution()
Wald or Inverse Gauss distribution.
The Wald (Inverse Gauss) cumulative distribution function.
weibull(number(), number() | Keyword.t()) :: distribution()
The Weibull distribution.
The Weibull cumulative distribution function.