extremevalues (version 1.0)

getLimit: 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

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 $f(y)=\lambda\exp(-\lambda y)$
• 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 $\lambda$ for weibull distribution

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:

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);