probabilityDensityFunction
30
triples
GPTKB property
Random triples
| Subject | Object |
|---|---|
| gptkb:Lorentzian_distribution | f(x; x0, γ) = [1/π] [γ / ((x - x0)^2 + γ^2)] |
| gptkb:Extreme_Value_Type_I_distribution | f(x) = (1/β) exp(-(x-μ)/β) exp(-exp(-(x-μ)/β)) |
| gptkb:Cauchy_distribution | f(x; x0, γ) = [1/(πγ)] [γ^2 / ((x - x0)^2 + γ^2)] |
| gptkb:Log-normal_distribution | f(x; μ, σ) = (1/(xσ√(2π))) exp(-(ln x - μ)^2/(2σ^2)), x > 0 |
| gptkb:Pearson_Type_I_distribution | f(x) = C (x-a)^{m-1} (b-x)^{n-1} |
| gptkb:Dirichlet_distribution | f(x;α) = (1/B(α)) ∏ x_i^{α_i-1} |
| gptkb:Gumbel_distribution | f(x) = (1/β) exp(-(z + exp(-z))) where z = (x - μ)/β |
| 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:Wigner_semicircle_distribution | (1/(2πR^2)) * sqrt(4R^2 - x^2) |
| gptkb:log-normal_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:multivariate_normal_distribution | f(x) = (1/((2π)^{k/2} |Σ|^{1/2})) exp(-1/2 (x-μ)^T Σ^{-1} (x-μ)) |
| gptkb:von_Mises_distribution | f(x|μ,κ) = exp(κ cos(x-μ)) / (2π I0(κ)) |
| gptkb:Rayleigh_distribution | (x/σ^2) * exp(-x^2/(2σ^2)) for x ≥ 0 |
| 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: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:circular_normal_distribution | f(θ; μ, κ) = [exp(κ cos(θ - μ))] / [2π I₀(κ)] |