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Modeling income on the basis of distribution mixture

100%
Sitek G.
Mathematical Economics
|
2014
|
issue 10(17)
79-90
EN
Finite mixtures of probability distributions may be successfully used in the modeling of probability distributions of incomes. These distributions are typically heavy tailed and positively skewed. This article deals with the problem of determining the number of components in mixture modeling. This paper considers the likelihood of ratio-based testing of the null hypothesis of homogeneity in mixture models. The number of components is an important parameter in the applications of finite mixture models.
2
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Estimation of regression parameters of two dimensional probability distribution mixtures

100%
Sitek G.
Studia Ekonomiczne
|
2016
|
vol. 304
30-46
EN
We use two methods of estimation parameters in a mixture regression: maximum likelihood (MLE) and the least squares method for an implicit interdependence. The most popular method for maximum likelihood esti-mation of the parameter vector is the EM algorithm. The least squares method for an implicit interdependence is based solving systems of nonlinear equations. Most frequently used method in the estimation of parameters mixtures regression is the method of maximum likelihood. The article presents the possibility of using a different the least squares method for an implicit interdependence and compare it with the maximum likelihood method. We compare accuracy of two methods of estimation by simulation using bias: root mean square error and bootstrapping standard errors of estimation.
PL
Do estymacji parametrów mieszanek regresji stosujemy dwie metody: metodę największej wiarygodności oraz metodę najmniejszych kwadratów dla zależności niejawnych. Najbardziej popularną metodą polegającą na maksymalizacji funkcji wiarygodności jest algorytm EM. Metoda najmniejszych kwadratów dla zależności niejawnych polega na rozwiązaniu układu równań nieliniowych. Najczęściej stosowaną metodą estymacji parametrów mieszanek regresji jest metoda największej wiarygodności. W artykule pokazano możliwość zastosowania innej metody najmniejszych kwadratów dla zależności niejawnych. Obie metody porównujemy symulacyjnie, używając obciążenia estymatora, pierwiastka błędu średniokwadratowego estymatora oraz bootstrapowe błędy standardowe.
3
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The Notion of the Diameter of Mereological Ball in Tarski's Geometry of Solids

100%
Sitek G.
Logic and Logical Philosophy
|
2017
|
vol. 26
|
issue 4
531–562
EN
In the paper "Full development of Tarski's geometry of solids" Gruszczyński and Pietruszczak have obtained the full development of Tarski’s geometry of solids that was sketched in [14, 15]. In this paper 1 we introduce in Tarski’s theory the notion of congruence of mereological balls and then the notion of diameter of mereological ball. We prove many facts about these new concepts, e.g., we give a characterization of mereological balls in terms of its center and diameter and we prove that the set of all diameters together with the relation of inequality of diameters is the dense linearly ordered set without the least and the greatest element.
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