getQQLimit: Determine outlier limit

Description Usage Arguments Details Value Author(s) References Examples

Description

Determine outlier limit. These functions are called by the wrapper function getOutliersII

Usage

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qqExponentialLimit(y, p, iLambda, alpha)
qqLognormalLimit(y, p , iLambda, alpha)
qqParetoLimit(y, p , iLambda, alpha)
qqWeibullLimit(y, p , iLambda, alpha)
qqNormalLimit(y, p , iLambda, alpha)

Arguments

y

Vector of real numbers

p

Corresponding quantile values

N

Index vector, indicating which elements of y should be used in the fit

rho

Confidence values for residual distribution

Details

The functions fit a model cdf to the observed y and p and returns the confidence limits for the fit residuals.

Value

limit

The residual-values corresponding to the confidence values

R2

R-squared value for the fit

lamda

(exponential only) Estimated location (and spread) parameter for f(y)=λ\exp(-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

M.P.J. van der Loo, Distribution based outlier detection for univariate data. Discussion paper 10003, Statistics Netherlands, The Hague (2010). Available from www.markvanderloo.eu or www.cbs.nl.

Examples

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y <- sort(exp(rnorm(100)));
p <- seq(1,100)/1000;
L <- qqExponentialLimit(y,p,seq(10,90),0.05);

extremevalues documentation built on May 2, 2019, 7:09 a.m.