cQuantGH function

Estimator of large quantiles using censored Hill

Estimator of large quantiles using censored Hill

Computes estimates of large quantiles Q(1p)Q(1-p) using the estimates for the EVI obtained from the generalised Hill estimator adapted for right censoring.

cQuantGH(data, censored, gamma1, p, plot = FALSE, add = FALSE, main = "Estimates of extreme quantile", ...)

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.
  • p: The exceedance probability of the quantile (we estimate Q(1p)Q(1-p) for pp small).
  • 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 extreme quantile".
  • ...: Additional arguments for the plot function, see plot for more details.

Details

The quantile is estimated as

Q^(1p)=Znk,n+ak,n(((1km)/p)γ^11)/γ^1) \hat{Q}(1-p)= Z_{n-k,n} + a_{k,n} ( ( (1-km)/p)^{\hat{\gamma}_1} -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(1SZ,k,n)/p^k a_{k,n} = Z_{n-k,n} H_{k,n} (1-S_{Z,k,n}) / \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, and

SZ,k,n=1(1M12/M2)(1)/2 S_{Z,k,n} = 1 - (1-M_1^2/M_2)^(-1) / 2

with

Ml==1/kj=1k(logXnj+1,nlogXnk,n)l. M_l = =1/k\sum_{j=1}^k (\log X_{n-j+1,n}- \log X_{n-k,n})^l.

Returns

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

  • Q: Vector of the corresponding quantile estimates.

  • p: The used exceedance probability.

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

cProbGH, cgenHill, QuantGH, Quant, 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) # Large quantile p <- 10^(-4) cQuantGH(Z, gamma1=cghill$gamma, censored=censored, p=p, plot=TRUE)
  • Maintainer: Tom Reynkens
  • License: GPL (>= 2)
  • Last published: 2024-12-02