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

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  • Misztal Małgorzata

    (University of Lodz, Lodz, Poland)

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.

Suggested Citation

  • Misztal Małgorzata, 2019. "On the Potential for Using Selected PCA-Based Methods to Analyze the Crime Rate in Poland," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(2), pages 15-32, June.
    • Handle: RePEc:vrs:eaiada:v:23:y:2019:i:2:p:15-32:n:2
    DOI: 10.15611/eada.2019.2.02
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    More about this item

    Keywords

    crime; criminal offence; multivariate exploratory data analysis; principal component analysis; factorial maps;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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