probabilityDensityFunction

30 triples
GPTKB property

Random triples
Subject Object
gptkb:Type_II_extreme_value_distribution f(x) = (α/s)((x-m)/s)^-(1+α) exp(-((x-m)/s)^-α) for x > m
gptkb:von_Mises_distribution f(x|μ,κ) = exp(κ cos(x-μ)) / (2π I0(κ))
gptkb:Gumbel_distribution f(x) = (1/β) exp(-(z + exp(-z))) where z = (x - μ)/β
gptkb:inverse_Wishart_distribution matrix-valued function
gptkb:Gaussian_Noise f(x) = (1/(σ√(2π))) * exp(- (x-μ)² / (2σ²))
gptkb:Gaussian_distribution f(x) = (1/(σ√(2π))) * exp(- (x-μ)^2 / (2σ^2))
gptkb:lognormal_distribution f(x; μ, σ) = (1/(xσ√(2π))) exp(-(ln x - μ)^2/(2σ^2)), x > 0
gptkb:Wigner_semicircle_distribution (1/(2πR^2)) * sqrt(4R^2 - x^2)
gptkb:Dirichlet_distribution f(x;α) = (1/B(α)) ∏ x_i^{α_i-1}
gptkb:Cauchy_distribution f(x; x0, γ) = [1/(πγ)] [γ^2 / ((x - x0)^2 + γ^2)]
gptkb:double_exponential_distribution f(x|μ,b) = (1/(2b)) * exp(-|x-μ|/b)
gptkb:Inverse_gamma_distribution (β^α / Γ(α)) x^(-α-1) exp(-β/x)
gptkb:generalized_extreme_value_distribution f(x) = (1/σ) [1 + ξ((x-μ)/σ)]^{-1/ξ-1} exp(-[1 + ξ((x-μ)/σ)]^{-1/ξ})
gptkb:GEV_distribution closed form
gptkb:Gaussian_Distribution f(x) = (1/(σ√(2π))) * exp(- (x-μ)^2 / (2σ^2))
gptkb:circular_normal_distribution f(θ; μ, κ) = [exp(κ cos(θ - μ))] / [2π I₀(κ)]
gptkb:Johnson_SU_distribution involves hyperbolic sine
gptkb:Pearson_Type_I_distribution f(x) = C (x-a)^{m-1} (b-x)^{n-1}
gptkb:Lorentzian_distribution f(x; x0, γ) = [1/π] [γ / ((x - x0)^2 + γ^2)]
gptkb:Arcsin_distribution f(x) = 1 / (π√(x(1-x))) for x in (0,1)

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