getLimit {extremevalues}R Documentation

Determine outlier limit

Description

Determine outlier limit. These functions are called by the wrapperfunction getOutlierLimit

Usage

getExponentialLimit(y, p, N, rho)
getLognormalLimit(y, p, N, rho)
getParetoLimit(y, p, N, rho)
getWeibullLimit(y, p, N, rho)
getNormalLimit(y, p, N, rho)

Arguments

y Vector of one-dimensional nonnegative data
p Corresponding quantile values
N Number of observations
rho Limiting expexted value

Details

The functions fit a model cdf to the observed y and p and returns the y-value above which less than rho values are expected, given N observations. See getOutlierLimit for a complete explanation.

The function returns a list with the following entries:

Value

limit The y-value above which less then rho observations are expected
R2 R-squared value for the fit
nFit Number of values used in fit (length(y))
lamda (exponential only) Estimated location (and spread) parameter for f(y)=λexp(-λ y)
mu (lognormal only) Estimated {sf E}(ln(y)) for lognormal distribution
sigma (lognormal only) Estimated Var(ln(y)) for lognormal distribution
ym (pareto only) Estimated location parameter (mode) for pareto distribution
alpha (pareto only) Estimated spread parameter for pareto distribution
k (weibull only) estimated power parameter k for weibull distribution
lambda (weibull only) estimated scaling parameter λ for weibull distribution

Author(s)

Mark van der Loo, see www.markvanderloo.eu

References

An outlier detection method for economic data, M.P.J. van der Loo, Submitted to The Journal of Official Statistics (November 2009)

Examples

y <- 10^rnorm(50);
p <- seq(1,50)/50;
L <- getExponentialLimit(y[10:48],p[10:48],50,0.5);

[Package extremevalues version 1.0 Index]