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gptkb:gamma_distribution
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f(x;k,θ) = x^{k-1} e^{-x/θ} / (θ^k Γ(k))
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gptkb:Onyx_Boox_Max_3
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yes
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gptkb:Johnson_SB_distribution
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f(x) = (delta / (lambda * sqrt(2*pi))) * [1 / (y*(1-y))] * exp(-0.5 * [gamma + delta * ln(y/(1-y))]^2), where y = (x - xi)/lambda
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gptkb:Standard_Normal_Distribution
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(1/√(2π)) * exp(-x²/2)
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gptkb:Variance_Gamma_distribution
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complex formula involving modified Bessel function
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gptkb:beta_distribution
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x^(alpha-1) * (1-x)^(beta-1) / B(alpha, beta)
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gptkb:Pearson_Type_IX_distribution
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complex formula involving beta function
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gptkb:chi-squared_distribution
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(1/(2^{k/2}Γ(k/2))) x^{(k/2)-1} e^{-x/2}
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gptkb:Gamma_distribution
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f(x;k,θ) = x^{k-1} e^{-x/θ} / (θ^k Γ(k)), x > 0
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gptkb:Inception_v1
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https://arxiv.org/abs/1409.4842
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gptkb:Pearson_Type_VI_distribution
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f(x; α1, α2, β) = (x/β)^{α1-1} / [β B(α1, α2) (1 + x/β)^{α1+α2}] for x > 0
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gptkb:Pearson_Type_0_distribution
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normal distribution PDF
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gptkb:univariate_t-distribution
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f(x) = Γ((ν+1)/2) / (√(νπ) Γ(ν/2)) (1 + x²/ν)^(-(ν+1)/2)
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gptkb:Onyx_Boox_Max_Lumi
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yes
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gptkb:Noncentral_chi-squared_distribution
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Involves modified Bessel function
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gptkb:arXiv:1810.09434
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https://arxiv.org/pdf/1810.09434.pdf
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gptkb:Fisher–Snedecor_distribution
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f(x; d1, d2) = [d1^{d1/2} d2^{d2/2} x^{(d1/2)-1}] / [B(d1/2, d2/2) (d1 x + d2)^{(d1+d2)/2}]
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gptkb:Inverse_chi-squared_distribution
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f(x; ν) = (2^{−ν/2}/Γ(ν/2)) x^{−(ν/2)−1} exp(−1/(2x))
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gptkb:Noncentral_t-distribution
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involves infinite sum
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gptkb:DINOv2
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https://arxiv.org/abs/2304.07193
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