Class ACERFunction

  • All Implemented Interfaces:
    Function<Vector,​Double>, RealScalarFunction, UnivariateRealFunction

    public class ACERFunction
    extends AbstractUnivariateRealFunction
    The ACER (Average Conditional Exceedance Rate) function \(\epsilon_k(\eta)\) approximates the probability \[ \epsilon_k(\eta) = Pr(X_k > \eta | X_1 \le \eta, X_2 \le \eta, ..., X_{k-1} \le \eta) \] for a sequence of stochastic process observations \(X_i\) with a k-step memory.

    The function is of the form (Gumbel-type): \[ \hat{\epsilon_k}(\eta) = q_k exp(-a_k (\eta - b_k)^{c_k}), \eta \ge \eta_1 \]

    The R equivalent function is acer::acer.evaluate. Note: R defines the conditional of epsilon using "less than" but this implementation sticks to the original paper which uses "less than or equal to".

    • Method Detail

      • evaluate

        public double evaluate​(double eta)
        Compute the epsilon value.
        Parameters:
        eta - the barrier level \(\eta\)
        Returns:
        the epsilon