Stan Math Library  2.10.0
reverse mode automatic differentiation
grad_reg_inc_beta.hpp
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1 #ifndef STAN_MATH_PRIM_SCAL_FUN_GRAD_REG_INC_BETA_HPP
2 #define STAN_MATH_PRIM_SCAL_FUN_GRAD_REG_INC_BETA_HPP
3 
7 #include <cmath>
8 
9 namespace stan {
10  namespace math {
11 
12  // Gradient of the regularized incomplete beta function ibeta(a, b, z)
13  template<typename T>
14  void grad_reg_inc_beta(T& g1, T& g2, T a, T b, T z,
15  T digammaA, T digammaB, T digammaSum, T betaAB) {
18  using std::exp;
19  using stan::math::lbeta;
20 
21  T dBda = 0;
22  T dBdb = 0;
23  grad_inc_beta(dBda, dBdb, a, b, z);
24  T b1 = exp(lbeta(a, b)) * inc_beta(a, b, z);
25  g1 = (dBda - b1 * (digammaA - digammaSum)) / betaAB;
26  g2 = (dBdb - b1 * (digammaB - digammaSum)) / betaAB;
27  }
28 
29  }
30 }
31 #endif
fvar< T > lbeta(const fvar< T > &x1, const fvar< T > &x2)
Definition: lbeta.hpp:16
fvar< T > inc_beta(const fvar< T > &a, const fvar< T > &b, const fvar< T > &x)
Definition: inc_beta.hpp:20
void grad_inc_beta(stan::math::fvar< T > &g1, stan::math::fvar< T > &g2, stan::math::fvar< T > a, stan::math::fvar< T > b, stan::math::fvar< T > z)
fvar< T > exp(const fvar< T > &x)
Definition: exp.hpp:10
void grad_reg_inc_beta(T &g1, T &g2, T a, T b, T z, T digammaA, T digammaB, T digammaSum, T betaAB)

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