cumulativeDistributionFunction

87 triples
GPTKB property

Alternative names (3)
CDF cdf cumulative distribution function

Random triples
Subject Object
gptkb:uniform_distribution (x-a)/(b-a) for a ≤ x ≤ b
gptkb:Erlang_distribution 1 - Σ_{n=0}^{k-1} e^{-λx} (λx)^n / n!
gptkb:Bernoulli_random_variable F(x) = 0 for x < 0, 1-p for 0 ≤ x < 1, 1 for x ≥ 1
gptkb:Standard_Normal_Distribution Φ(x)
gptkb:Inverse_chi-squared_distribution F(x; ν) = Γ(ν/2, 1/(2x))/Γ(ν/2)
gptkb:Weibull_distribution_(with_shape_parameter_1) F(x) = 1 - exp(-x/λ) for x ≥ 0
gptkb:von_Mises_distribution no closed form
gptkb:Binomial_distribution Sum_{i=0}^k C(n, i) p^i (1-p)^{n-i}
gptkb:Rayleigh_distribution 1 - exp(-x^2/(2σ^2)) for x ≥ 0
gptkb:Laplace_distribution 0.5 * exp((x-μ)/b) for x<μ, 1-0.5*exp(-(x-μ)/b) for x≥μ
gptkb:circular_normal_distribution no closed form
gptkb:Chi-squared_distribution P(x; k) = γ(k/2, x/2)/Γ(k/2)
gptkb:beta_distribution regularized incomplete beta function
gptkb:Gumbel_distribution F(x) = exp(-exp(-(x-μ)/β))
gptkb:log-normal_distribution Φ((ln x - μ)/σ), x > 0
gptkb:geometric_distribution P(X ≤ k) = 1 - (1-p)^k
gptkb:Weibull_distribution F(x; k, λ) = 1 - e^{-(x/λ)^k} for x ≥ 0
gptkb:Lévy_distribution F(x; μ, c) = erfc(sqrt(c / (2(x-μ)))), x > μ
gptkb:Fréchet_distribution F(x; α, s, m) = exp(-((x-m)/s)^(-α)) for x > m
gptkb:chi-squared_distribution γ(k/2, x/2)/Γ(k/2)

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