R: Threshold Estimation Approaches

# Threshold Estimation Approaches

## Documentation for package ‘tea’ version 1.1

- DESCRIPTION file

## Help Pages

tea-package | Threshold Estimation Approaches
althill | Alternative Hill Plot
avhill | Averaged Hill Plot
dAMSE | Minimizing the AMSE of the Hill estimator with respect to k
danielsson | A Double Bootstrap Procedure for Choosing the Optimal Sample Fraction
danish | Danish Fire Insurance Claims
dgpd | The Generalized Pareto Distribution (GPD)
DK | A Bias-based procedure for Choosing the Optimal Sample Fraction
eye | Automated Approach for Interpreting the Hill-Plot
ggplot | Gerstengarbe Plot
GH | A Bias-based procedure for Choosing the Optimal Threshold
gomes | A Double Bootstrap Procedure for Choosing the Optimal Sample Fraction
gpd | The Generalized Pareto Distribution (GPD)
gpdFit | Parameter estimation for the Generalized Pareto Distribution (GPD)
hall | A Single Bootstrap Procedure for Choosing the Optimal Sample Fraction
Himp | A Single Bootstrap Procedure for Choosing the Optimal Sample Fraction
HW | Minimizing the AMSE of the Hill estimator with respect to k
mindist | Minimizing the distance between the empirical tail and a theoretical Pareto tail with respect to k.
pgpd | The Generalized Pareto Distribution (GPD)
PS | Sample Path Stability Algorithm
qgpd | The Generalized Pareto Distribution (GPD)
qqestplot | QQ-Estimator-Plot
qqgpd | QQ-Plot against the generalized Pareto distribution for given number of exceedances
rgpd | The Generalized Pareto Distribution (GPD)
RT | Adaptive choice of the optimal sample fraction in tail index estimation
sumplot | Sum Plot
tea | Threshold Estimation Approaches
TH | Sequential Goodness of Fit Testing for the Generalized Pareto Distribution