#ifndef STAN_MATH_PRIM_SCAL_FUN_INV_LOGIT_HPP
#define STAN_MATH_PRIM_SCAL_FUN_INV_LOGIT_HPP

#include <cmath>

namespace stan {
namespace math {

/**
 * Returns the inverse logit function applied to the argument.
 *
 * The inverse logit function is defined by
 *
 * \f$\mbox{logit}^{-1}(x) = \frac{1}{1 + \exp(-x)}\f$.
 *
 * This function can be used to implement the inverse link function
 * for logistic regression.
 *
 * The inverse to this function is <code>logit</code>.
 *
 *
 \f[
 \mbox{inv\_logit}(y) =
 \begin{cases}
 \mbox{logit}^{-1}(y) & \mbox{if } -\infty\leq y \leq \infty \\[6pt]
 \textrm{NaN} & \mbox{if } y = \textrm{NaN}
 \end{cases}
 \f]

 \f[
 \frac{\partial\, \mbox{inv\_logit}(y)}{\partial y} =
 \begin{cases}
 \frac{\partial\, \mbox{logit}^{-1}(y)}{\partial y} & \mbox{if } -\infty\leq
 y\leq \infty \\[6pt] \textrm{NaN} & \mbox{if } y = \textrm{NaN} \end{cases} \f]

 \f[
 \mbox{logit}^{-1}(y) = \frac{1}{1 + \exp(-y)}
 \f]

 \f[
 \frac{\partial \, \mbox{logit}^{-1}(y)}{\partial y} =
 \frac{\exp(y)}{(\exp(y)+1)^2} \f]
 *
 * @param a Argument.
 * @return Inverse logit of argument.
 */
inline double inv_logit(double a) {
  using std::exp;
  return 1.0 / (1.0 + exp(-a));
}

}  // namespace math
}  // namespace stan
#endif
