Automatic Differentiation
 
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◆ estimate_with_err_check()

template<size_t ErrIndex, size_t NestedIndex = 0, GradientCalc GradW7 = GradientCalc::OFF, bool LogResult = true, typename F , typename T_err , typename... ArgsTupleT>
auto stan::math::internal::estimate_with_err_check ( F &&  functor,
T_err &&  err,
ArgsTupleT &&...  args_tuple 
)
inline

Utility function for estimating a function with a given set of arguments, checking the result against a provided error tolerance, and re-estimating the function with the increased error if it fails.

Template Parameters
ErrIndexPosition of the error argument in the provided arguments
GradW7Whether the gradient of w is computed
NestedIndexNested position if the error argument is within a tuple
LogResultWhether result is on log- or on natural-scale
FType of functor
T_errtype of error
ArgsTupleTType of tuple of arguments for functor
Parameters
functorFunction to apply
errError value to check against
args_tupleTuple of arguments to pass to functor

Definition at line 632 of file wiener5_lpdf.hpp.