Stan Math Library
4.9.0
Automatic Differentiation
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return_type_t< T_theta, std::vector< T_lam > > stan::math::log_mix | ( | const T_theta & | theta, |
const std::vector< T_lam > & | lambda | ||
) |
Return the log mixture density given specified mixing proportions and array of log density vectors.
\[ \frac{\partial }{\partial p_x}\left[ \log\left(\exp^{\log\left(p_1\right)+d_1}+\cdot\cdot\cdot+ \exp^{\log\left(p_n\right)+d_n}\right)+ \log\left(\exp^{\log\left(p_1\right)+f_1}+\cdot\cdot\cdot+ \exp^{\log\left(p_n\right)+f_n}\right)\right] =\frac{e^{d_x}}{e^{d_1}p_1+\cdot\cdot\cdot+e^{d_m}p_m}+ \frac{e^{f_x}}{e^{f_1}p_1+\cdot\cdot\cdot+e^{f_m}p_m} \]
\[ \frac{\partial }{\partial d_x}\left[ \log\left(\exp^{\log\left(p_1\right)+d_1}+\cdot\cdot\cdot+ \exp^{\log\left(p_n\right)+d_n}\right) +\log\left(\exp^{\log\left(p_1\right)+f_1}+\cdot\cdot\cdot+ \exp^{\log\left(p_n\right)+f_n}\right)\right] =\frac{e^{d_x}p_x}{e^{d_1}p_1+\cdot\cdot\cdot+e^{d_m}p_m} \]
T_theta | Type of theta. This can be a scalar, std vector or row/column vector |
T_lam | Type of vector in std vector lambda. This can be std vector or row/column vector. |
theta | std/row/col vector of mixing proportions in [0, 1]. |
lambda | std vector containing std/row/col vectors of log densities. |
Definition at line 144 of file log_mix.hpp.