@misc{Misztal_Małgorzata_On_2019,
 author={Misztal, Małgorzata},
 identifier={DOI: 10.15611/eada.2019.2.02},
 year={2019},
 rights={Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={Econometrics = Ekonometria, 2019, Vol. 23, No. 2, s. 15-32},
 language={eng},
 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},
 title={On the potential for using selected PCA-based methods to analyze the crime rate in Poland},
 type={artykuł},
 keywords={crime, criminal offence, multivariate exploratory data analysis, principal component analysis, factorial maps, przestępczość, przestępstwa kryminalne, wielowymiarowa eksploracyjna analiza danych, analiza głównych składowych, mapy czynnikowe},
}