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Metody pro stanovení počtu shluků ve statistických programových systémech
Řezanková, H. ; Húsek, Dušan
The paper deals with approaches to determination of the optimal number of groups of objects when objects are clustered by different methods implemented in commercial statistical software packages. These approaches are applied to the example of finding groups of deputies of the Russian parliament on the base of roll-call votes in 2004. The capabilities of software packages S-PLUS, SAS, SPSS, and SYSTAT are compared.
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Informační shlukování kategoriálních dat
Hora, Jan
The EM algorithm has been used repeatedly to identify latent classes in categorical data by estimating finite distribution mixtures of product components. Unfortunately, the underlying mixtures are not uniquely identifiable and, moreover, the estimated mixture parameters are starting-point dependent. For this reason we use the latent class model only to define a set of ``elementary'' classes by estimating a mixture of a large number components. As such a mixture we use also an optimally smoothed kernel estimate. We propose a hierarchical ``bottom up'' cluster analysis based on unifying the elementary latent classes sequentially. The clustering procedure is controlled by minimum information loss criterion.
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Psychosemantic methods: between qualitative and quantitative approaches
Urbánek, Tomáš
Psychosemantic methods can be loosely defined as methods enabling to examine or measure various features of the human psyche in some way, mostly by means of assessing the similarities or differences between meanings, assigned by examinees to the stimuli used in these methods.These methods can be used for illustration of the possible connection between qualitative and quantitative methodologies, since the data obtained this way can be quantitatively analysed and interpreted both on the level of indvidual and /or appropriately selected group of individuals. An example of the psychosemantic method in this article is the Semantic selection test.
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Shluková analýza pro náhodné procesy událostí
Volf, Petr
The paper deals with the statistical analysis of unemployment data. The data are modeled via a discrete-time version of Poisson process. Cluster analysis is employed for selection of sub-populations with similar development of unemployment in recent years. Inside these clusters, an additional analysis of heterogeneity is performed. Numerical example analyzes certain aspects of unemployment development in the Czech Republic in 1993-1998.
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Riders
Sviták, David ; Hebák, Petr (advisor) ; Kocúrová, Barbora (referee)
Riders are growing more important as a part of insurance markets. The aim of this thesis is to introduce riders offered by a chosen insurance company in the Czech Republic. The next part is dedicated to the study of a structure of arranged riders in one year. A characteristic of riders and main covers a, which affect the number of arranged riders, are specified by using statistical methods. In the last part, clients are classified based on their owned riders by using cluster analysis. This thesis contains some recommenddations to create new riders.
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