probabilityDensityFunction

30 triples
GPTKB property

Random triples
Subject Object
gptkb:GEV_distribution closed form
gptkb:double_exponential_distribution f(x|μ,b) = (1/(2b)) * exp(-|x-μ|/b)
gptkb:Extreme_Value_Type_I_distribution f(x) = (1/β) exp(-(x-μ)/β) exp(-exp(-(x-μ)/β))
gptkb:inverse_Wishart_distribution matrix-valued function
gptkb:Arcsine_distribution_(when_alpha=beta=0.5) f(x) = 1 / (π√(x(1-x))) for 0 < x < 1
gptkb:normal_distribution_(precision_parameter) f(x) = sqrt(τ/2π) * exp(-τ/2 * (x-μ)^2)
gptkb:lognormal_distribution f(x; μ, σ) = (1/(xσ√(2π))) exp(-(ln x - μ)^2/(2σ^2)), x > 0
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:Inverse_gamma_distribution (β^α / Γ(α)) x^(-α-1) exp(-β/x)
gptkb:multivariate_normal_distribution f(x) = (1/((2π)^{k/2} |Σ|^{1/2})) exp(-1/2 (x-μ)^T Σ^{-1} (x-μ))
gptkb:Gaussian_distribution f(x) = (1/(σ√(2π))) * exp(- (x-μ)^2 / (2σ^2))
gptkb:Log-normal_distribution f(x; μ, σ) = (1/(xσ√(2π))) exp(-(ln x - μ)^2/(2σ^2)), x > 0
gptkb:Rayleigh_distribution (x/σ^2) * exp(-x^2/(2σ^2)) for x ≥ 0
gptkb:Gaussian_Distribution f(x) = (1/(σ√(2π))) * exp(- (x-μ)^2 / (2σ^2))
gptkb:Pearson_Type_I_distribution f(x) = C (x-a)^{m-1} (b-x)^{n-1}
gptkb:Arcsin_distribution f(x) = 1 / (π√(x(1-x))) for x in (0,1)
gptkb:Wigner_semicircle_distribution (1/(2πR^2)) * sqrt(4R^2 - x^2)
gptkb:Cauchy_distribution f(x; x0, γ) = [1/(πγ)] [γ^2 / ((x - x0)^2 + γ^2)]
gptkb:Pareto_distribution f(x; xm, α) = α xm^α / x^(α+1)

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