Time series assessment in the era of Stockholm Convention & GMP

Interactive publication

This interactive web publication will guide you through an entire process of data analysis on time series of persistent organic pollutants (POPs) carried out in a framework of the GENASIS project. The analysis consists of eight steps - from visual inspection of the data to obtaining the final results of descriptive statistics and trend tests. Each step is supplemented by an interactive example, where all the methods, R source code and several descriptions, comments and notes are available for hands-on training and practice.

R source code

Each of the eight consequent steps of the data analysis is equipped with an R source code, which is partially compatible with the interactive example for the particular step. Most of the source codes use functions and methods from the R package genasis, developped in order to simplify and unify POPs data processing. This package shares several methods with the Global Monitoring Plan (GMP) methodology on POPs monitoring data processing. The genasis R package is freely available on CRAN repository web page.

Interactive examples

Demonstrative interactive examples were developed in order to allow the user trying all the described methods on his/her own in a real time. They are very intuitive and easy to manage even without any knowledge of R or another statistical software. All the examples include plots to emonstrate how the functions work and a brief legend on the methods used. The examples are accesible via the square tiles below the text.

The Shiny R package was used to create all the examples.

Authors

Jiří Kalina, Jiří Jarkovský, Ladislav Dušek, Jana Klánová, Jana Borůvková, Ivo Šnábl and Roman Šmíd

Institute of Biostatisic and analyses &

Research Centre for Toxic Compounds in the Environment

Masaryk University

Kamenice 126/3

625 00 Brno

Czech Republic

 

kalina@iba.muni.cz

Eight steps of data analysis

Direct links to examples based on R + Shiny

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2: Treatment of values under LoQ
2: Treatment of values under LoQ
3: Outliers exclusion
3: Outliers exclusion
4: Passives recalculation
4: Passives recalculation
1: Visual inspection
1: Visual inspection
2: Treatment of values under LoQ
2: Treatment of values under LoQ
3: Outliers exclusion
3: Outliers exclusion
4: Passives recalculation
4: Passives recalculation
5: Seasonality analysis
5: Seasonality analysis
3: Outliers exclusion
3: Outliers exclusion
4: Passives recalculation
4: Passives recalculation
5: Seasonality analysis
5: Seasonality analysis
6: Annual aggregation
6: Annual aggregation
4: Passives recalculation
4: Passives recalculation
5: Seasonality analysis
5: Seasonality analysis
6: Annual aggregation
6: Annual aggregation
7: Descriptive statistics
7: Descriptive statistics
5: Seasonality analysis
5: Seasonality analysis
6: Annual aggregation
6: Annual aggregation
7: Descriptive statistics
7: Descriptive statistics
8: Trend analysis
8: Trend analysis
6: Annual aggregation
6: Annual aggregation
7: Descriptive statistics
7: Descriptive statistics
8: Trend analysis
8: Trend analysis
1: Visual inspection
1: Visual inspection
7: Descriptive statistics
7: Descriptive statistics
8: Trend analysis
8: Trend analysis
2: Treatment of values under LoQ
2: Treatment of values under LoQ
1: Visual inspection
1: Visual inspection
8: Trend analysis
8: Trend analysis
2: Treatment of values under LoQ
2: Treatment of values under LoQ
3: Outliers exclusion
3: Outliers exclusion
1: Visual inspection
1: Visual inspection