Automatic Differentiation
 
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◆ positive_constrain() [3/3]

template<bool Jacobian, typename T , require_not_std_vector_t< T > * = nullptr>
auto stan::math::positive_constrain ( const T &  x,
return_type_t< T > &  lp 
)
inline

Return the positive value for the specified unconstrained input.

If the Jacobian parameter is true, the log density accumulator is incremented with the log absolute Jacobian determinant of the transform. All of the transforms are specified with their Jacobians in the Stan Reference Manual chapter Constraint Transforms.

Template Parameters
Jacobianif true, increment log density accumulator with log absolute Jacobian determinant of constraining transform
TA type inheriting from Eigen::EigenBase, a var_value with inner type inheriting from Eigen::EigenBase, a standard vector, or a scalar
Parameters
xunconstrained value or container
[in,out]lplog density accumulator
Returns
positive constrained version of unconstrained value(s)

If the Jacobian parameter is true, the log density accumulator is incremented with the log absolute Jacobian determinant of the transform. All of the transforms are specified with their Jacobians in the Stan Reference Manual chapter Constraint Transforms.

Template Parameters
Jacobianif true, increment log density accumulator with log absolute Jacobian determinant of constraining transform
TA standard vector with inner type inheriting from Eigen::EigenBase, a var_value with inner type inheriting from Eigen::EigenBase, a standard vector, or a scalar
Parameters
xunconstrained value or container
[in,out]lplog density accumulator
Returns
positive constrained version of unconstrained value(s)

Definition at line 65 of file positive_constrain.hpp.