lb_constrain() [2/14]

template<typename T , typename L , require_all_kernel_expressions_and_none_scalar_t< T > * = nullptr, require_all_kernel_expressions_t< L > * = nullptr>

auto stan::math::lb_constrain ( const T &  x, const L &  lb, return_type_t< T, L > &  lp  )

inline

Return the lower-bounded value for the specified unconstrained input and specified lower bound.

Specialization of lb_constrain to apply a matrix of lower bounds elementwise to each input element.

Return the lower-bounded value for the specified unconstrained input and specified lower bound, incrementing the specified reference with the log absolute Jacobian determinant of the transform.

The transform applied is

\(f(x) = \exp(x) + L\)

where \(L\) is the constant lower bound.

Template Parameters

T	kernel generator expression
L	kernel generator expression

Parameters

[in]	x	unconstrained input
[in]	lb	lower bound
[in,out]	lp	reference to log probability to increment

Returns

constrained matrix

Template Parameters

T	Scalar.
L	Scalar.

Parameters

[in]	x	unconstrained input
[in]	lb	lower bound on output
[in,out]	lp	reference to log probability to increment

Returns

lower-bound constrained value corresponding to inputs

Template Parameters

T	A type inheriting from EigenBase.
L	A type inheriting from EigenBase.

Parameters

[in]	x	unconstrained input
[in]	lb	lower bound on output
[in,out]	lp	reference to log probability to increment

Returns

lower-bound constrained value corresponding to inputs

Template Parameters

T	A type inheriting from EigenBase or a var_value with inner type inheriting from EigenBase.
L	A type inheriting from EigenBase or a var_value with inner type inheriting from EigenBase.

Parameters

[in]	x	unconstrained input
[in]	lb	lower bound on output
[in,out]	lp	reference to log probability to increment

Returns

lower-bound constrained value corresponding to inputs

Definition at line 60 of file lb_constrain.hpp.