Stan Math Library
5.0.0
Automatic Differentiation
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The inverse of the normalized incomplete beta function of a, b, with probability p.
Used to compute the inverse cumulative density function for the beta distribution.
\[ \frac{\partial }{\partial a} = (1-w)^{1-b}w^{1-a} \left( w^a\Gamma(a)^2 {}_3\tilde{F}_2(a,a,1-b;a+1,a+1;w) - B(a,b)I_w(a,b)\left(\log(w)-\psi(a) + \psi(a+b)\right) \right)/;w=I_z^{-1}(a,b) \]
\[ \frac{\partial }{\partial b} = (1-w)^{-b}w^{1-a}(w-1) \left( (1-w)^{b}\Gamma(b)^2 {}_3\tilde{F}_2(b,b,1-a;b+1,b+1;1-w) - B_{1-w}(b,a)\left(\log(1-w)-\psi(b) + \psi(a+b)\right) \right)/;w=I_z^{-1}(a,b) \]
\[ \frac{\partial }{\partial z} = (1-w)^{1-b}w^{1-a}B(a,b)/;w=I_z^{-1}(a,b) \]
a | Shape parameter a >= 0; a and b can't both be 0 |
b | Shape parameter b >= 0 |
p | Random variate. 0 <= p <= 1 |
if | constraints are violated or if any argument is NaN |
Definition at line 60 of file inv_inc_beta.hpp.