|
gptkb:log-normal_distribution
|
(exp(σ^2) + 2)√(exp(σ^2) - 1)
|
|
gptkb:univariate_t-distribution
|
0 (for df > 3)
|
|
gptkb:gamma_distribution
|
2/√k
|
|
gptkb:Extreme_Value_Type_I_distribution
|
12√6 ζ(3)/π^3 ≈ 1.1396
|
|
gptkb:Laplace_distribution
|
0
|
|
gptkb:Rademacher_distribution
|
0
|
|
gptkb:Standard_uniform_distribution
|
0
|
|
gptkb:Fréchet_distribution
|
exists for α > 3
|
|
gptkb:multivariate_normal_distribution
|
0
|
|
gptkb:Pearson_type_III_distribution
|
can be positive or negative
|
|
gptkb:Student's_t-distribution_(ν=1)
|
0
|
|
gptkb:Type_II_extreme_value_distribution
|
positive
|
|
gptkb:triangular_distribution
|
depends on parameters
|
|
gptkb:Normal_distribution_(precision_parameterization)
|
0
|
|
gptkb:gamma_distribution_(with_shape_n)
|
2 / sqrt(n)
|
|
gptkb:exponential_distribution
|
2
|
|
gptkb:circular_normal_distribution
|
zero (symmetric distribution)
|
|
gptkb:Rayleigh_distribution
|
0.6311
|
|
gptkb:Pearson_Type_I
|
can be positive or negative
|
|
gptkb:Chi-squared_distribution
|
sqrt(8/k)
|