Automatic Differentiation
 
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◆ uniform_lpdf() [2/3]

template<bool propto, typename T_y , typename T_low , typename T_high , require_all_not_nonscalar_prim_or_rev_kernel_expression_t< T_y, T_low, T_high > * = nullptr>
return_type_t< T_y, T_low, T_high > stan::math::uniform_lpdf ( const T_y &  y,
const T_low &  alpha,
const T_high &  beta 
)

The log of a uniform density for the given y, lower, and upper bound.

\begin{eqnarray*} y &\sim& \mbox{\sf{U}}(\alpha, \beta) \\ \log (p (y \, |\, \alpha, \beta)) &=& \log \left( \frac{1}{\beta-\alpha} \right) \\ &=& \log (1) - \log (\beta - \alpha) \\ &=& -\log (\beta - \alpha) \\ & & \mathrm{ where } \; y \in [\alpha, \beta], \log(0) \; \mathrm{otherwise} \end{eqnarray*}

Template Parameters
T_ytype of scalar
T_lowtype of lower bound
T_hightype of upper bound
Parameters
yA scalar variable.
alphaLower bound.
betaUpper bound.
Exceptions
std::invalid_argumentif the lower bound is greater than or equal to the lower bound

Definition at line 47 of file uniform_lpdf.hpp.