extremis (version 1.2.1)

cdf: Empirical Scedasis Distribution Function

Description

This function computes the empirical scedasis distribution function.

Usage

cdf(Y, threshold = quantile(Y[, 2], 0.95))

Value

C

empirical scedasis distribution function.

w

standardized indices of exceedances.

k

number of exceedances above a threshold.

Y

raw data.

The plot method depicts the empirical cumulative scedasis function, and the reference line for the case of constant frequency of extremes over time (if uniform = TRUE).

Arguments

Y

data frame from which the estimate is to be computed; first column corresponds to time and the second to the variable of interest.

threshold

value used to threshold the data y; by default threshold = quantile(Y[, 2], 0.95).

Author

Miguel de Carvalho

Details

The empirical scedasis distribution function was introduced by Einmahl et al (2016).

References

Einmahl, J. H., Haan, L., and Zhou, C. (2016) Statistics of heteroscedastic extremes. Journal of the Royal Statistical Society: Ser. B, 78(1), 31--51.

Examples

data(sp500)
attach(sp500)
Y <- data.frame(date[-1], -diff(log(close)))
fit <- cdf(Y)
plot(fit)
plot(fit, original = FALSE)