Hi all,
Just a seed for statistical purposes
Plugin handles primitives listed below:
Sample Estimators
Mean("matrix") - Returns the arithmetic mean from a sample.
GeometricMean("matrix") - Returns the geometric mean from a sample.
HarmonicMean("matrix") - Returns the harmonic mean from a sample.
WeightedMean("1:matrix", "2:matrix") - Returns the weighted arithmetic mean from a sample "1:matrix" and a corresponding weight "2:matrix".
Median("matrix") - Returns the median value from a sample.
Mode("matrix") - Returns the mode value from a sample.
Mode("1:matrix", "2:variable") - Returns the mode value from a sample and the number of occourrences.
Moment("1:matrix", "2:number") - Returns the "2:number"th central moment of a sample "1:matrix".
StdDev("matrix") - Returns the unbiased standard deviation from a sample "1:matrix".
Variance("matrix") - Returns the unbiased variance from a sample "1:matrix".
Skewness("matrix") - Returns the g₁ skewness from a sample (biased).
Kurtosis("matrix") - Returns the β₂ kurtosis from a sample.
KurtosisExcess("matrix") - Returns the γ₂ kurtosis excess from a sample.
Intercept("1:matrix", "2:matrix") - Returns the intercept of the straight line given by a simple linear regression from a data points "1:matrix","2:matrix".
Slope("1:matrix", "2:matrix") - Returns the slope of the straight line given by a simple linear regression from a data points "1:matrix","2:matrix".
Probability Density Functions
pdf.Binomial("1:number", "2:number") - Returns the Binomial pdf of k successes with "1:number" trials and "2:number" success probability ∈[0;1] in each trial.
pdf.Binomial("1:number", "2:number", "3:number") - Returns the Binomial pdf value of "1:number" successes with "2:number" trials and "3:number" success probability ∈[0;1] in each trial.
pdf.Cauchy("variable") - Returns the Standard Cauchy pdf (x.0 = 0 and γ = 1) evaluated in "1:variable" points.
pdf.Cauchy("1:variable", "2:number", "3:number") - Returns the Cauchy pdf evaluated in "1:variable" points, using assigned "2:number" location parameter and the "3:number" scale parameter.
pdf.ChiSquare("variable") - Returns the Χ² single degree of freedom pdf evaluated in "1:variable" points.
pdf.ChiSquare("1:variable", "2:number") - Returns the Χ² pdf evaluated in "1:variable" points, using assigned "2:number" degrees of freedom.
pdf.Exponential("variable") - Returns the Standard Exponential pdf (λ = 1) evaluated in "1:variable" points.
pdf.Exponential("1:variable", "2:number") - Returns the Exponential pdf in "1:variable" points, using assigned "2:number" rate parameter.
pdf.F("variable") - Returns the Fisher-Snedecor F single degree of freedom pdf evaluated in "1:variable".
pdf.F("1:variable", "2:number", "3:number") - Returns the Fisher-Snedecor F pdf evaluated in "1:variable" points, using assigned "2:number" numerator and "3:number" denominator degrees of freedom.
pdf.Geometric("1:variable", "2:number") - Returns the Geometric pdf of failures until the first success, for "1:variable" trials ∈[0;n] and single trial success probability "2:number" ∈(0;1].
pdf.GeometricShifted("1:variable", "2:number") - Returns the Geometric pdf used for modeling the number of trials until the first success, for "1:variable" trials ∈[1;n] and single trial success probability "2:number" ∈(0;1].
pdf.Normal("variable") - Returns the Standard Normal pdf (null mean and unitary standard deviation) evaluated in "1:variable" points.
pdf.Normal("1:variable", "2:number") - Returns the Normal pdf evaluated in "1:variable" points, using assigned "2:number" mean and unitary standard deviation.
pdf.Normal("1:variable", "2:number", "3:number") - Returns the Normal pdf evaluated in "1:variable" points, using assigned "2:number" mean and "3:number" as standard deviation.
pdf.Poisson("variable") - Returns the Standard Poisson pdf (λ = 1) evaluated in "1:variable" points.
pdf.Poisson("1:variable", "2:number") - Returns the Poisson pdf evaluated in "1:variable" points, using assigned "2:number" as expected value.
pdf.Rayleigh("variable") - Returns the Standard Rayleigh pdf (σ = 1) evaluated in "1:variable" points.
pdf.Rayleigh("1:variable", "2:number") - Returns the Rayleigh pdf evaluated in "1:variable" points, using assigned "2:number" as standard deviation.
pdf.t("variable") - Returns the Student's t single degree of freedom pdf evaluated in "1:variable" points.
pdf.t("1:variable", "2:number") - Returns the Student's t pdf evaluated in "1:variable" points, using assigned "2:number" degrees of freedom.
pdf.Uniform("1:variable", "2:number", "3:number") - Returns the Uniform Continuous pdf evaluated in "1:variable" points, inside the ["2:number","3:number"] interval of values.
pdf.UniformDiscrete("1:variable", "2:number", "3:number") - Returns the Uniform Discrete pdf evaluated in "1:variable" points, inside the ["2:number","3:number"] interval of values.
pdf.Weibull("variable") - Returns the Standard Weibull pdf (λ = 1 and k = 1) evaluated in "1:variable" points.
pdf.Weibull("1:variable", "2:number", "3:number") - Returns the Weibull pdf evaluated in "1:variable" points, using assigned "2:number" scale parameter and the "3:number" shape parameter.
Cumulative Density Functions
CDF.Binomial("1:number", "2:number") - Returns the Binomial CDF of k successes with "1:number" trials and "2:number" success probability ∈[0;1] in each trial.
CDF.Binomial("1:number", "2:number", "3:number") - Returns the Binomial CDF value of "1:number" successes with "2:number" trials and "3:number" success probability ∈[0;1] in each trial.
CDF.Cauchy("variable") - Returns the Standard Cauchy CDF (x.0 = 0 and γ = 1) evaluated in "1:variable" points.
CDF.Cauchy("1:variable", "2:number", "3:number") - Returns the Cauchy CDF evaluated in "1:variable" points, using assigned "2:number" location parameter and the "3:number" scale parameter.
CDF.ChiSquare("variable") - Returns the Χ² single degree of freedom CDF evaluated in "1:variable" points.
CDF.ChiSquare("1:variable", "2:number") - Returns the Χ² CDF evaluated in "1:variable" points, using assigned "2:number" degrees of freedom.
CDF.Exponential("variable") - Returns the Standard Exponential CDF (λ = 1) evaluated in "1:variable" points.
CDF.Exponential("1:variable", "2:number") - Returns the Exponential CDF evaluated in "1:variable" points, using assigned "2:number" rate parameter.
CDF.F("variable") - Returns the Fisher-Snedecor F single degree of freedom CDF evaluated in "1:variable".
CDF.F("1:variable", "2:number", "3:number") - Returns the Fisher-Snedecor F CDF evaluated in "1:variable" points, using assigned "2:number" numerator and "3:number" denominator degrees of freedom.
CDF.Geometric("1:variable", "2:number") - Returns the Geometric CDF of failures until the first success, for "1:variable" trials ∈[0;n] and single trial success probability "2:number" ∈(0;1].
CDF.GeometricShifted("1:variable", "2:number") - Returns the Geometric Shifted CDF used for modeling the number of trials until the first success, for "1:variable" trials ∈[1;n] and single trial success probability "2:number" ∈(0;1].
CDF.Normal("variable") - Returns the Standard Normal CDF (null mean and unitary standard deviation) evaluated in "1:variable" points.
CDF.Normal("1:variable", "2:number") - Returns the Normal CDF evaluated in "1:variable" points, using assigned "2:number" mean and unitary standard deviation.
CDF.Normal("1:variable", "2:number", "3:number") - Returns the Normal CDF evaluated in "1:variable" points, using assigned "2:number" mean and "3:number" as standard deviation.
CDF.Poisson("variable") - Returns the Standard Poisson CDF (λ = 1) evaluated in "1:variable" points.
CDF.Poisson("1:variable", "2:number") - Returns the Poisson CDF evaluated in "1:variable" points, using assigned "2:number" as expected value.
CDF.Rayleigh("variable") - Returns the Standard Rayleigh CDF (σ = 1) evaluated in "1:variable" points.
CDF.Rayleigh("1:variable", "2:number") - Returns the Rayleigh CDF evaluated in "1:variable" points, using assigned "2:number" as standard deviation.
CDF.t("variable") - Returns the Student's t single degree of freedom CDF evaluated in "1:variable" points.
CDF.t("1:variable", "2:number") - Returns the Student's t CDF evaluated in "1:variable" points, using assigned "2:number" degrees of freedom.
CDF.Uniform("1:variable", "2:number", "3:number") - Returns the Uniform Continuous CDF evaluated in "1:variable" points, inside the ["2:number","3:number"] interval of values.
CDF.UniformDiscrete("1:variable", "2:number", "3:number") - Returns the Uniform Discrete CDF evaluated in "1:variable" points, inside the ["2:number","3:number"] interval of values.
CDF.Weibull("variable") - Returns the Standard Weibull CDF (λ = 1 and k = 1) evaluated in "1:variable" points.
CDF.Weibull("1:variable", "2:number", "3:number") - Returns the Weibull CDF evaluated in "1:variable" points, using assigned "2:number" scale parameter and the "3:number" shape parameter.
Quantile functions
ICDF.Binomial("1:number", "2:number", "3:number") - Returns the Binomial quantile function for "1:number" probability values ∈[0;1] with "2:number" trials and "3:number" success probability ∈[0;1] in each trial.
ICDF.Cauchy("variable") - Returns the Standard Cauchy quantile function (x.0 = 0 and γ = 1) evaluated for "1:variable" probability values ∈[0;1].
ICDF.Cauchy("1:variable", "2:number", "3:number") - Returns the Cauchy quantile function evaluated for "1:variable" probability values ∈[0;1], using assigned "2:number" location parameter and the "3:number" scale parameter.
ICDF.Exponential("variable") - Returns the Standard Exponential quantile function (λ = 1) evaluated for "1:variable" probability values ∈[0;1].
ICDF.ChiSquare("1:variable") - Returns the single degree of freedom Χ² quantile function evaluated for "1:variable" probability values ∈[0;1].
ICDF.ChiSquare("1:variable", "2:number") - Returns the single degree of freedom Χ² quantile function evaluated for "1:variable" probability values ∈[0;1], using assigned "2:number" degrees of freedom.
ICDF.F("1:variable") - Returns the single degree of freedom Fisher-Snedecor F quantile function evaluated for "1:variable" probability values ∈[0;1].
ICDF.F("1:variable", "2:number", "3:number") - Returns the single degree of freedom Fisher-Snedecor F quantile function evaluated for "1:variable" probability values ∈[0;1], "2:number" numerator and "3:number" denominator degrees of freedom.
ICDF.Exponential("1:variable", "2:number") - Returns the Exponential quantile function evaluated for "1:variable" probability values ∈[0;1], using assigned "2:number" rate parameter.
ICDF.Geometric("1:variable", "2:number") - Returns the Geometric quantile function, for "1:variable" probability values ∈(0;1] to observe n successes with single trial probability "2:number" ∈(0;1].
ICDF.GeometricShifted("1:variable", "2:number") - Returns the Geometric Shifted quantile function used for modeling the number of trials until the first success, for "1:variable" probability values ∈(0;1] to observe n failures until the first success with single trial probability "2:number" ∈(0;1].
ICDF.Normal("variable") - Returns the Standard Normal quantile function (null mean and unitary standard deviation) evaluated for "1:variable" probability values ∈[0;1].
ICDF.Normal("1:variable", "2:number") - Returns the Normal quantile function evaluated for "1:variable" probability values ∈[0;1], using assigned "2:number" mean and unitary standard deviation.
ICDF.Normal("1:variable", "2:number", "3:number") - Returns the Normal quantile function evaluated for "1:variable" probability values, using assigned "2:number" mean and "3:number" as standard deviation.
ICDF.Poisson("variable") - Returns the Standard quantile function (λ = 1) evaluated for "1:variable" probability values.
ICDF.Poisson("1:variable", "2:number") - Returns the Poisson quantile function evaluated for "1:variable" probability values ∈[0;1], using assigned "2:number" as expected value.
ICDF.Rayleigh("variable") - Returns the Standard Rayleigh quantile function (σ = 1) evaluated for "1:variable" probability values ∈[0;1].
ICDF.Rayleigh("1:variable", "2:number") - Returns the Rayleigh quantile function evaluated for "1:variable" probability values ∈[0;1], using assigned "2:number" as standard deviation.
ICDF.t("1:variable") - Returns the Standard Student's t quantile function (ν = 1) evaluated for "1:variable" probability values ∈[0;1].
ICDF.t("1:variable", "2:number") - Returns the Student's t quantile function evaluated for "1:variable" probability values ∈[0;1], using assigned "2:number" degrees of freedom (ν).
ICDF.Uniform("1:variable", "2:number", "3:number") - Returns the Uniform Continuous quantile function evaluated for "1:variable" probability values ∈[0;1], inside the ["2:number","3:number"] interval of values.
ICDF.UniformDiscrete("1:variable", "2:number", "3:number") - Returns the Uniform Discrete quantile function evaluated for "1:variable" probability values ∈[0;1], inside the ["2:number","3:number"] interval of values.
ICDF.Weibull("variable") - Returns the Standard Weibull quantile function (λ = 1 and k = 1) evaluated for "1:variable" probability values ∈[0;1].
ICDF.Weibull("1:variable", "2:number", "3:number") - Returns the Weibull quantile function evaluated for "1:variable" probability values ∈[0;1], using assigned "2:number" scale parameter and the "3:number" shape parameter.
Random Numbers
Random("number") - Returns a vector containing "1:number" of random values between 0 and 1 with uniform distribution.
Random("1:number", "2:number") - Returns a "1:number" x "2:number" rectangular matrix containing random values between 0 and 1 with uniform distribution.
Random.N("1:number", "2:number") - Returns a random value between "1:number" and "2:number" with uniform distribution. "1:number" and "2:number" must be between -2147483648 and 2147483646.
Random.N("1:number", "2:number", "3:number") - Returns a vector containing "1:number" of random values between "2:number" and "3:number" with uniform distribution. "2:number" and "3:number" must be between -2147483648 and 2147483646.
Random.N("1:number", "2:number", "3:number", "4:number") - Returns a "1:number" x "2:number" rectangular matrix containing random values between "3:number" and "4:number" with uniform distribution. "3:number" and "4:number" must be between -2147483648 and 2147483646.
Tools
Beta("1:variable", "2:variable") - Returns the Beta function of "1:variable" and "2:variable" positive parameters.
BetaRegularized("1:variable", "2:variable", "3:variable") - Returns the Regularized Beta function evaluated in "1:variable" ∈[0;1], using "2:variable" and "3:variable" positive parameters.
GammaRegularized.P("1:variable", "2:variable") - Regularized Gamma function P(a,x):γ(a,x)/Γ(a).
GammaRegularized.Q("1:variable", "2:variable") - Regularized Gamma function Q(a,x):Γ(a,x)/Γ(a).
Dirac("variable") - Dirac delta function, evaluated in "1:variable" points.
Dirac("1:variable", "2:number") - Dirac delta function, evaluated in "1:variable" points and shifted in the "2:number" point.
erf("variable") - Approximated error function (Abramowitz and Stegun - max error: 1.5E-7), evaluated in "1:variable" points.
erf("1:variable", "2:number") - Approximated error function (Abramowitz and Stegun - max error: 1.5E-7), evaluated in "1:variable" points and shifted in the "2:number" point.
erfc("variable") - Approximated complementary error function (Abramowitz and Stegun - max error: 1.5E-7), evaluated in "1:variable" points.
erfc("1:variable", "2:number") - Approximated complementary error function (Abramowitz and Stegun - max error: 1.5E-7), evaluated in "1:variable" points and shifted in the "2:number" point.
erfinv("variable") - Approximated inverse error function, evaluated in "1:variable" points.
Heaviside("variable") - Heaviside step function, evaluated in "1:variable" points.
Heaviside("1:variable", "2:number") - Heaviside step function, evaluated in "1:variable" points and shifted in the "2:number" point.
Heaviside.D("variable") - Discrete Heaviside step function, evaluated in "1:variable" points.
Heaviside.D("1:variable", "2:number") - Discrete Heaviside step function, evaluated in "1:variable" points and shifted in the "2:number" point.
Ceil("variable") - Ceil function. Returns the smallest integer greater than or equal to "1:variable".
Floor("variable") - Floor function. Returns the largest integer less than or equal to "1:variable".
PLEASE REPORT HERE ANY ISSUE.requirements: .Net Framework 3.5 (Windows) / Mono 2.0 (Linux) / SMath Studio 0.97.5581
installation: Tools > Plugins > change "Local Storage" to "Online Gallery" > Statistical Tools
sources: if you want to see the plugin sources,
look in the SVN repository.
embedded plugins: Meta Numerics library 2.2.1.0 (
website,
license)
Edited by user 15 September 2015 16:31:42(UTC)
| Reason: Meta Numerics
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