由Davide Carpi (davide.carpi@gmail.com)在SMath项目的作用域中创建。由smath发布。
这是一个开源项目。MIT许可证下共享的源代码SVN存储库

Features of Statistical Tools

Functions (112 items):

  • Bessel("1:number", "2:number") — Bessel function and derivatives of "1:number" order, evaluated in the "2:number" point; returns Jnu(x), J'nu(x), Ynu(x), and Y'nu(x).
  • BesselJ("1:number", "2:number") — Bessel function of the First Kind, of "1:number" order, evaluated in the "2:number" point.
  • BesselY("1:number", "2:number") — Bessel function of the Second Kind, of "1:number" order, evaluated in the "2:number" point.
  • 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.
  • 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 (null location parameter and unitary scale parameter) 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.
  • 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") — Error function, evaluated in "1:variable" points.
  • erf("1:variable", "2:number") — Error function, evaluated in "1:variable" points and shifted in the "2:number" point.
  • erfc("variable") — Complementary error function, evaluated in "1:variable" points.
  • erfc("1:variable", "2:number") — Complementary error function, evaluated in "1:variable" points and shifted in the "2:number" point.
  • erfinv("variable") — Inverse error function, evaluated in "1:variable" points.
  • 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).
  • GeometricMean("matrix") — Returns the geometric mean from a sample.
  • HarmonicMean("matrix") — Returns the harmonic mean from a sample.
  • 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.
  • 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.
  • 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 (null location parameter and unitary scale parameter) 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.ChiSquare("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.Exponential("variable") — Returns the Standard Exponential quantile function (λ = 1) evaluated for "1:variable" probability values ∈[0;1].
  • 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.F("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.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("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.
  • 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".
  • Kurtosis("matrix") — Returns the β₂ kurtosis from a sample.
  • KurtosisExcess("matrix") — Returns the γ₂ kurtosis excess from a sample.
  • Mean("matrix") — Returns the arithmetic mean from a sample.
  • 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".
  • 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 (null location parameter and unitary scale parameter) 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.
  • 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.
  • 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.
  • Skewness("matrix") — Returns the g₁ skewness from a sample (biased).
  • 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".
  • StdDev("matrix") — Returns the unbiased standard deviation from a sample "1:matrix".
  • Variance("matrix") — Returns the unbiased variance from a sample "1:matrix".
  • WeightedMean("1:matrix", "2:matrix") — Returns the weighted arithmetic mean from a sample "1:matrix" and a corresponding weight "2:matrix".