On the potential for using selected PCA-based methods to analyze the crime rate in Poland

• Authors: Małgorzata Misztal
• Languages of publication: EN

Abstracts

EN

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.

Keywords

EN

crime; criminal offence; multivariate exploratory data analysis; principal component analysis; factorial maps

• Publisher: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Econometrics. Ekonometria. Advances in Applied Data Analytics
• Year: 2019
• Issue: vol. 23 no. 2
• Pages: 15-32

Contributors

author

Małgorzata Misztal