Automatic Differentiation
 
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◆ wiener_lccdf_defective() [2/2]

template<bool propto = false, typename T_y , typename T_a , typename T_t0 , typename T_w , typename T_v , typename T_sv , typename T_sw , typename T_st0 >
auto stan::math::wiener_lccdf_defective ( const T_y &  y,
const T_a &  a,
const T_t0 &  t0,
const T_w &  w,
const T_v &  v,
const T_sv &  sv,
const T_sw &  sw,
const T_st0 &  st0,
const double &  precision_derivatives = 1e-8 
)
inline

Returns the log CCDF of the Wiener distribution for a (Wiener) drift diffusion model with up to 7 parameters.

If containers are supplied, returns the log sum of the probabilities. See 'wiener_full_lpdf' for more comprehensive documentation As the CDF goes to the probability to hit the upper bound (instead of 1, as it is usually the case) when the reaction time goes to infinity, the CCDF is defined as ccdf = probability_to_hit_the_upper_bound - cdf.

Template Parameters
T_ytype of reaction time
T_atype of boundary separation
T_t0type of non-decision time
T_wtype of relative starting point
T_vtype of drift rate
T_svtype of inter-trial variability of drift rate
T_swtype of inter-trial variability of relative starting point
T_st0type of inter-trial variability of non-decision time
Parameters
yThe reaction time in seconds
aThe boundary separation
t0The non-decision time
wThe relative starting point
vThe drift rate
svThe inter-trial variability of the drift rate
swThe inter-trial variability of the relative starting point
st0The inter-trial variability of the non-decision time
precision_derivativesLevel of precision in estimation of partial derivatives
Returns
log probability or log sum of probabilities for upper boundary responses
Exceptions
std::domain_errorif non-decision time t0 is greater than reaction time y.
std::domain_errorif 1-sw/2 is smaller than or equal to w.
std::domain_errorif sw/2 is larger than or equal to w.

Definition at line 87 of file wiener_full_lccdf_defective.hpp.