cProbGH function

Estimator of small exceedance probabilities and large return periods using censored generalised Hill

Estimator of small exceedance probabilities and large return periods using censored generalised Hill

Computes estimates of a small exceedance probability P(X>q)P(X>q) or large return period 1/P(X>q)1/P(X>q) using the estimates for the EVI obtained from the generalised Hill estimator adapted for right censoring.

cProbGH(data, censored, gamma1, q, plot = FALSE, add = FALSE, main = "Estimates of small exceedance probability", ...) cReturnGH(data, censored, gamma1, q, plot = FALSE, add = FALSE, main = "Estimates of large return period", ...)

Arguments

  • data: Vector of nn observations.

  • censored: A logical vector of length nn indicating if an observation is censored.

  • gamma1: Vector of n1n-1 estimates for the EVI obtained from cgenHill.

  • q: The used large quantile (we estimate P(X>q)P(X>q) or 1/P(X>q)1/P(X>q) for qq large).

  • plot: Logical indicating if the estimates should be plotted as a function of kk, default is FALSE.

  • add: Logical indicating if the estimates should be added to an existing plot, default is FALSE.

  • main: Title for the plot, default is "Estimates of small exceedance probability" for cProbGH

    and "Estimates of large return period" for cReturnGH.

  • ...: Additional arguments for the plot function, see plot for more details.

Details

The probability is estimated as

P^(X>q)=(1km)×(1+γ^1/ak,n×(qZnk,n))1/γ^1 \hat{P}(X>q)=(1-km) \times (1+ \hat{\gamma}_1/a_{k,n} \times (q-Z_{n-k,n}))^{-1/\hat{\gamma}_1}

with Zi,nZ_{i,n} the ii-th order statistic of the data, γ^1\hat{\gamma}_1 the generalised Hill estimator adapted for right censoring and kmkm the Kaplan-Meier estimator for the CDF evaluated in Znk,nZ_{n-k,n}. The value aa is defined as

ak,n=Znk,nHk,n(1min(γ^1,0))/p^k a_{k,n} = Z_{n-k,n} H_{k,n} (1-\min(\hat{\gamma}_1,0)) / \hat{p}_k

with Hk,nH_{k,n} the ordinary Hill estimator and p^k\hat{p}_k the proportion of the kk largest observations that is non-censored.

Returns

A list with following components: - k: Vector of the values of the tail parameter kk.

  • P: Vector of the corresponding probability estimates, only returned for cProbGH.

  • R: Vector of the corresponding estimates for the return period, only returned for cReturnGH.

  • q: The used large quantile.

References

Einmahl, J.H.J., Fils-Villetard, A. and Guillou, A. (2008). "Statistics of Extremes Under Random Censoring." Bernoulli, 14, 207--227.

Author(s)

Tom Reynkens

See Also

cQuantGH, cgenHill, ProbGH, cProbMOM, KaplanMeier

Examples

# Set seed set.seed(29072016) # Pareto random sample X <- rpareto(500, shape=2) # Censoring variable Y <- rpareto(500, shape=1) # Observed sample Z <- pmin(X, Y) # Censoring indicator censored <- (X>Y) # Generalised Hill estimator adapted for right censoring cghill <- cgenHill(Z, censored=censored, plot=TRUE) # Small exceedance probability q <- 10 cProbGH(Z, censored=censored, gamma1=cghill$gamma1, q=q, plot=TRUE) # Return period cReturnGH(Z, censored=censored, gamma1=cghill$gamma1, q=q, plot=TRUE)
  • Maintainer: Tom Reynkens
  • License: GPL (>= 2)
  • Last published: 2024-12-02