getQQLimit {extremevalues} | R Documentation |
Determine outlier limit
Description
Determine outlier limit. These functions are called by the wrapper function getOutliersII
Usage
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 |
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 |
mu |
(lognormal only) Estimated |
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 |
lambda |
(weibull only) estimated scaling parameter |
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
y <- sort(exp(rnorm(100)));
p <- seq(1,100)/1000;
L <- qqExponentialLimit(y,p,seq(10,90),0.05);