<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The aim of the paper is to assess the potential for using some selected PCA-based methods to analyze the spatial diversity of crime in Poland during 2000-2017. Classical principal components analysis (PCA) deals with two-way matrices, usually taking into account objects and variables. In the case of data analyzed in the study, apart from two dimensions (<italic>objects</italic> – voivodships, <italic>variables</italic><bold>–</bold> criminal offences), there is also the dimension of time, so the dataset can be seen as data cube: <italic>objects</italic> × <italic>variables</italic> × <italic>time</italic>. Therefore, this type of data requires the use of methods handling three-way data structures. In the paper the variability of some selected categories of criminal offences in time (2000–2017) and space (according to voivodships) is analyzed using the between-class and the within-class principal component analysis. The advantage of these methods is, among others, the possibility of the graphical presentation of the results in two-dimensional space with the use of factorial maps.</p></abstract>

The aim of the paper is to assess the potential for using some selected PCA-based methods to analyze the spatial diversity of crime in Poland during 2000-2017. Classical principal components analysis (PCA) deals with two-way matrices, usually taking into account objects and variables. In the case of data analyzed in the study, apart from two dimensions (objects – voivodships, variables– criminal offences), there is also the dimension of time, so the dataset can be seen as data cube: objects × variables × time. Therefore, this type of data requires the use of methods handling three-way data structures. In the paper the variability of some selected categories of criminal offences in time (2000–2017) and space (according to voivodships) is analyzed using the between-class and the within-class principal component analysis. The advantage of these methods is, among others, the possibility of the graphical presentation of the results in two-dimensional space with the use of factorial maps.

On the Potential for Using Selected PCA-Based Methods to Analyze the Crime Rate in Poland

Econometrics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The aim of the paper is to assess the potential for using some selected PCA-based methods to analyze the spatial diversity of crime in Poland during 2000-2017....

On the Potential for Using Selected PCA-Based Methods to Analyze the Crime Rate in Poland

Data publikacji: 26 cze 2019

Zakres stron: 15 - 32

DOI: https://doi.org/10.15611/eada.2019.2.02

Słowa kluczowe
crime, criminal offence, multivariate exploratory data analysis, principal component analysis, factorial maps

© 2019 Małgorzata Misztal, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

On the Potential for Using Selected PCA-Based Methods to Analyze the Crime Rate in Poland

Data publikacji: 26 cze 2019

Zakres stron: 15 - 32

DOI: https://doi.org/10.15611/eada.2019.2.02

Słowa kluczowecrime, criminal offence, multivariate exploratory data analysis, principal component analysis, factorial maps

© 2019 Małgorzata Misztal, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
crime, criminal offence, multivariate exploratory data analysis, principal component analysis, factorial maps