Documentation
¶
Overview ¶
F-distribution, alias Fisher-Snedecor distribution
Index ¶
- Variables
- func Bernoulli(ρ float64) func() int64
- func Bernoulli_CDF(ρ float64) func(k int64) float64
- func Bernoulli_LnPMF(ρ float64) func(k int64) float64
- func Bernoulli_PMF(ρ float64) func(k int64) float64
- func Bernoulli_PMF_At(ρ float64, k int64) float64
- func Beta(α float64, β float64) func() float64
- func BetaInv_CDF(α, β float64) func(p float64) float64
- func BetaInv_CDF_For(α, β, p float64) float64
- func Beta_CDF(α float64, β float64) func(x float64) float64
- func Beta_CDF_At(α, β, x float64) float64
- func Beta_LnPDF(α float64, β float64) func(x float64) float64
- func Beta_PDF(α float64, β float64) func(x float64) float64
- func Beta_PDF_At(α, β, x float64) float64
- func Binom_p_ConfI(n int64, p, alpha float64) (float64, float64)
- func Binomial(ρ float64, n int64) func() int64
- func Binomial_CDF(ρ float64, n int64) func(k int64) float64
- func Binomial_CDF_At(ρ float64, n, k int64) float64
- func Binomial_CDF_trivial(ρ float64, n int64) func(k int64) float64
- func Binomial_LnPMF(ρ float64, n int64) func(i int64) float64
- func Binomial_PMF(ρ float64, n int64) func(i int64) float64
- func Binomial_PMF_At(ρ float64, n, k int64) float64
- func CRP_LnPMF(α float64) func(x []int64) float64
- func CRP_PMF(α float64) func(x []int64) float64
- func Choice(θ []float64) func() int64
- func Choice_LnPMF(θ []float64) func(i int64) float64
- func Choice_PMF(θ []float64) func(i int64) float64
- func Dirichlet(α []float64) func() []float64
- func Dirichlet_LnPDF(α []float64) func(x []float64) float64
- func Dirichlet_PDF(α []float64) func(θ []float64) float64
- func Exp(λ float64) func() float64
- func Exp_LnPDF(λ float64) func(x float64) float64
- func Exp_PDF(λ float64) func(x float64) float64
- func F(d1 int64, d2 int64) func() float64
- func F_CDF(df1, df2 float64) func(x float64) float64
- func F_CDF_At(df1, df2, x float64) float64
- func F_InvCDF(df1, df2 float64) func(p float64) float64
- func F_InvCDF_For(df1, df2, p float64) float64
- func F_LnPDF(d1 float64, d2 float64) func(x float64) float64
- func F_PDF(d1 float64, d2 float64) func(x float64) float64
- func Gamma(α float64, λ float64) func() float64
- func Gamma_CDF(k float64, θ float64) func(x float64) float64
- func Gamma_CDF_At(k, θ, x float64) float64
- func Gamma_CDFint(k int64, θ float64) func(x float64) float64
- func Gamma_InvCDF(k float64, θ float64) func(x float64) float64
- func Gamma_InvCDF_For(k, θ, p float64) float64
- func Gamma_LnPDF(α float64, λ float64) func(x float64) float64
- func Gamma_PDF(k float64, θ float64) func(x float64) float64
- func Gamma_PDF_At(k, θ, x float64) float64
- func Geometric(ρ float64) func() int64
- func Geometric_LnPMF(ρ float64) func(i int64) float64
- func Geometric_PMF(ρ float64) func(i int64) float64
- func InvGamma_CDF(a, b float64) func(x float64) float64
- func InvGamma_CDF_At(a, b, x float64) float64
- func InvGamma_LnPDF(a, b float64) func(x float64) float64
- func InvGamma_PDF(a, b float64) func(x float64) float64
- func InvGamma_PDF_At(a, b float64) func(x float64) float64
- func LnPoisson_CDF_a(λ float64) func(k int64) float64
- func LnRange_PMF(n int64) func(i int64) float64
- func LogChoice(lws []float64) func() int64
- func Multinomial(θ []float64, n int64) func() []int64
- func Multinomial_LnPMF(θ []float64, n int64) func(x []int64) float64
- func Multinomial_PMF(θ []float64, n int64) func(x []int64) float64
- func NegativeBinomial(ρ float64, r int64) func() int64
- func NegativeBinomial_CDF(ρ float64, r int64) func(k int64) float64
- func NegativeBinomial_CDF_At(ρ float64, r, k int64) float64
- func NegativeBinomial_LnPMF(ρ float64, r int64) func(i int64) float64
- func NegativeBinomial_PMF(ρ float64, r int64) func(k int64) float64
- func NegativeBinomial_PMF_At(ρ float64, r, k int64) float64
- func NextBernoulli(ρ float64) int64
- func NextBeta(α float64, β float64) float64
- func NextBinomial(ρ float64, n int64) (result int64)
- func NextChoice(θ []float64) int64
- func NextDirichlet(α []float64) []float64
- func NextExp(λ float64) float64
- func NextF(d1 int64, d2 int64) float64
- func NextGamma(α float64, λ float64) float64
- func NextGeometric(ρ float64) int64
- func NextLogChoice(lws []float64) int64
- func NextMultinomial(θ []float64, n int64) []int64
- func NextNegativeBinomial(ρ float64, r int64) int64
- func NextNormal(μ float64, σ float64) float64
- func NextPoisson(λ float64) int64
- func NextRange(n int64) int64
- func NextStudentsT(ν float64) float64
- func NextXsquare(n int64) (x float64)
- func Normal(μ, σ float64) func() float64
- func NormalInv_CDF_For(p, sigma float64) float64
- func Normal_CDF(μ, σ float64) func(x float64) float64
- func Normal_LnPDF(μ float64, σ float64) func(x float64) float64
- func Normal_PDF(μ float64, σ float64) func(x float64) float64
- func Poisson(λ float64) func() int64
- func Poisson_CDF(λ float64) func(k int64) float64
- func Poisson_CDF_At(λ float64, k int64) float64
- func Poisson_CDF_a(λ float64) func(k int64) float64
- func Poisson_LnPMF(λ float64) func(k int64) float64
- func Poisson_PMF(λ float64) func(k int64) float64
- func Poisson_PMF_At(λ float64, k int64) float64
- func Range(n int64) func() int64
- func Range_PMF(n int64) func(i int64) float64
- func RejectionSample(targetDensity func(float64) float64, sourceDensity func(float64) float64, ...) float64
- func Shuffle(x []interface{})
- func ShuffleFloat64(x []float64)
- func ShuffleInt64(x []int64)
- func StudentsT(ν float64) func() float64
- func StudentsT_LnPDF(ν float64) func(x float64) float64
- func StudentsT_PDF(ν float64) func(x float64) float64
- func Uniform() func() float64
- func Uniform_LnPDF() func(x float64) float64
- func Uniform_PDF() func(x float64) float64
- func Xsquare(n int64) func() float64
- func Xsquare_CDF(n int64) func(p float64) float64
- func Xsquare_InvCDF(n int64) func(p float64) float64
- func Xsquare_LnPDF(n int64) func(x float64) float64
- func Xsquare_PDF(n int64) func(x float64) float64
- func Z_CDF() func(float64) float64
- func Z_CDF_At(x float64) float64
- func Z_InvCDF_For(p float64) float64
- func Z_PDF() func(float64) float64
- func Z_PDF_At(x float64) float64
Constants ¶
This section is empty.
Variables ¶
View Source
var NextUniform func() float64 = rand.Float64
Functions ¶
func Bernoulli_CDF ¶
func Bernoulli_LnPMF ¶
func Bernoulli_PMF ¶
func Bernoulli_PMF_At ¶
func BetaInv_CDF ¶
Inverse of the cumulative beta probability density function for a given probability.
p: Probability associated with the beta distribution α: Parameter of the distribution β: Parameter of the distribution A: Optional lower bound to the interval of x B: Optional upper bound to the interval of x
func BetaInv_CDF_For ¶
func Beta_CDF_At ¶
Value of CDF of Beta distribution(α, β) at x
func Beta_PDF_At ¶
Value of PDF of Beta distribution(α, β) at x
func Binomial_CDF ¶
Cumulative Distribution Function for the Binomial distribution
func Binomial_CDF_At ¶
func Binomial_CDF_trivial ¶
Cumulative Distribution Function for the Binomial distribution, trivial implementation
func Binomial_LnPMF ¶
Natural logarithm of Probability Mass Function for the Binomial distribution
func Binomial_PMF ¶
Probability Mass Function for the Binomial distribution
func Binomial_PMF_At ¶
func Choice_LnPMF ¶
func Choice_PMF ¶
func Dirichlet_LnPDF ¶
func Dirichlet_PDF ¶
func F_InvCDF_For ¶
Value of the inverse CDF of F-distribution for probability p
func Gamma_CDF_At ¶
Value of the cumulative distribution function at x
func Gamma_CDFint ¶
Cumulative distribution function, for integer k only
func Gamma_InvCDF ¶
Inverse CDF (Quantile) function
func Gamma_InvCDF_For ¶
Value of the inverse CDF for probability p
func Gamma_LnPDF ¶
Natural logarithm of the probability density function
func Gamma_PDF_At ¶
Value of the probability density function at x
func Geometric_LnPMF ¶
func Geometric_PMF ¶
func InvGamma_CDF ¶
Inverse Gamma distribution: cumulative distribution function
func InvGamma_CDF_At ¶
Inverse Gamma distribution: value of the cumulative distribution function at x
func InvGamma_LnPDF ¶
Inverse Gamma distribution: natural logarithm of the probability density function
func InvGamma_PDF ¶
Inverse Gamma distribution: probability density function
func InvGamma_PDF_At ¶
Inverse Gamma distribution: probability density function at x
func LnPoisson_CDF_a ¶
func LnRange_PMF ¶
func Multinomial ¶
func NegativeBinomial ¶
func NegativeBinomial_CDF_At ¶
func NegativeBinomial_PMF_At ¶
func NextBernoulli ¶
func NextBinomial ¶
func NextChoice ¶
func NextDirichlet ¶
func NextGeometric ¶
NextGeometric(ρ) => # of NextBernoulli(ρ) failures before one success
func NextLogChoice ¶
func NextMultinomial ¶
func NextNegativeBinomial ¶
NegativeBinomial(ρ, r) => number of NextBernoulli(ρ) failures before r successes
func NextNormal ¶
func NextPoisson ¶
func NextStudentsT ¶
StudentsT(ν) => N(0, 1)*sqrt(ν/NextGamma(ν/2, 2))
func NormalInv_CDF_For ¶
Inverse CDF of Normal distribution for probability p //// ??? only *sigma? from GSL
func Normal_CDF ¶
Cumulative Distribution Function for the Normal distribution
func Poisson_CDF ¶
func Poisson_CDF_At ¶
func Poisson_CDF_a ¶
func Poisson_LnPMF ¶
func Poisson_LnPMF(λ float64) (foo func(i int64) float64) {
pmf := Poisson_PMF(λ)
return func(i int64) (p float64) {
return log(pmf(i))
//p = -λ +log(λ)*float64(i)
//x := log(Γ(float64(i)+1))
//_ = x
//p -= LnΓ(float64(i)+1)
//return p
}
}
func Poisson_PMF ¶
func Poisson_PMF_At ¶
func RejectionSample ¶
func ShuffleFloat64 ¶
func ShuffleFloat64(x []float64)
func ShuffleInt64 ¶
func ShuffleInt64(x []int64)
func StudentsT_LnPDF ¶
func StudentsT_PDF ¶
func Uniform_LnPDF ¶
func Uniform_PDF ¶
func Xsquare_CDF ¶
Cumulative density function of the Chi-Squared distribution
func Xsquare_InvCDF ¶
Inverse CDF (Quantile) function of the Chi-Squared distribution
func Xsquare_LnPDF ¶
func Xsquare_PDF ¶
func Z_InvCDF_For ¶
Inverse CDF of Standard Normal distribution for probability p
Types ¶
This section is empty.
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