Methods for Identification of Outliers in Environmental Data
Box-Cox transformation of data - Only intended for developer use
Changepoint outlier detection plot - Only intended for developer use
Changepoint analysis - Only intended for developer use
Chebyshev inequality based identification of outliers on segments - On...
Limits for control chart R - Only intended for developer use
Limits for control chart s - Only intended for developer use
Limits for control chart x - Only intended for developer use
Control chart outliers detection plot - Only intended for developer us...
Extreme value outlier detection plot - Only intended for developer use
Extremal index estimation (Holesovsky and Fusek, 2020) - Only intended...
Extremal index estimation (Gomes, 1993) - Only intended for developer ...
Extremal index estimation (Ferro and Segers, 2003) - Only intended for...
Extremal index estimation (Suveges and Davison, 2010) - Only intended ...
Extremal index estimation (Smith and Weissman, 1994) - Only intended f...
Extremal index estimation (Northrop, 2015) - Only intended for develop...
Parameter alpha for Quantiles of normal distribution based outlier...
Parameter L for Chebyshev inequality based outlier detection - Only in...
Table of Control Charts Constants - Only intended for developer use
Grubbs test based identification of outliers on segments - Only intend...
Outlier detection using Grubbs test - Only intended for developer use
Identification of outliers using changepoint analysis
Identification of outliers using control charts
Identification of outliers using extreme value theory
Outlier detection plot
Left medcouple (LMC) - Only intended for developer use
Right medcouple (RMC) - Only intended for developer use
Robust medcouple MC-LR test - Only intended for developer use
Moment estimates of GP distribution parameters - Only intended for dev...
Mean residual life (MRL) plot
Normal distribution based identification of outliers on segments - Onl...
Outlier detection plot
Return level estimation - Only intended for developer use
Segment length control - Only intended for developer use
Kernel regression smoothing
Stability plot
Summary of the outlier detection results
Three semi-parametric methods for detection of outliers in environmental data based on kernel regression and subsequent analysis of smoothing residuals. The first method (Campulova, Michalek, Mikuska and Bokal (2018) <DOI: 10.1002/cem.2997>) analyzes the residuals using changepoint analysis, the second method is based on control charts (Campulova, Veselik and Michalek (2017) <DOI: 10.1016/j.apr.2017.01.004>) and the third method (Holesovsky, Campulova and Michalek (2018) <DOI: 10.1016/j.apr.2017.06.005>) analyzes the residuals using extreme value theory (Holesovsky, Campulova and Michalek (2018) <DOI: 10.1016/j.apr.2017.06.005>).