VOLUME 20 , ISSUE 4 (December 2019) - List of articles

MULTI-DOMAIN NEYMAN-TCHUPROV OPTIMAL ALLOCATION

Jacek Wesołowski

The eigenproblem solution of the multi-domain efﬁcient allocation is identiﬁed as a direct generalization of the classical Neyman-Tchuprov optimal allocation in stratiﬁed SRSWOR. This is achieved through analysis of eigenvalues and eigenvectors of a suitable population-based matrix D. Such a solution is an analytical companion to NLP approaches, which are often used in applications, see, e.g. Choudhry, Rao and Hidiroglou (2012). In this paper we are interested rather in the structure of the opti(..)

DOI: 10.21307/stattrans-2019-031

GENERAL LINEAR MODEL: AN EFFECTIVE TOOL FOR ANALYSIS OF CLAIM SEVERITY IN MOTOR THIRD PARTY LIABILITY INSURANCE

Erik Šoltés/ Silvia Zelinová/ Mária Bilíková

The paper focuses on the analysis of claim severity in motor third party liability insurance under the general linear model. The general linear model combines the analyses of variance and regression and makes it possible to measure the influence of categorical factors as well as the numerical explanatory variables on the target variable. In the paper, simple, main and interaction effects of relevant factors have been quantified using estimated regression coefficients and least squares means. Sta(..)

DOI: 10.21307/stattrans-2019-032

HYBRID MULTIPLE IMPUTATION IN A LARGE SCALE COMPLEX SURVEY

Humera Razzak/ Christian Heumann

Large-scale complex surveys typically contain a large number of variables measured on an even larger number of respondents. Missing data is a common problem in such surveys. Since usually most of the variables in a survey are categorical, multiple imputation requires robust methods for modelling high-dimensional categorical data distributions. This paper introduces the 3-stage Hybrid Multiple Imputation (HMI) approach, computationally efficient and easy to implement, to impute complex survey dat(..)

DOI: 10.21307/stattrans-2019-033

LINEAR CHOLESKY DECOMPOSITION OF COVARIANCE MATRICES IN MIXED MODELS WITH CORRELATED RANDOM EFFECTS

Anasu Rabe/ D. K. Shangodoyin/ K. Thaga

Modelling the covariance matrix in linear mixed models provides an additional advantage in making inference about subject-speciﬁc effects, particularly in the analysis of repeated measurement data, where time-ordering of the responses induces signiﬁcant correlation. Some difﬁculties encountered in these modelling procedures include high dimensionality and statistical interpretability of parameters, positive definiteness constraint and violation of model assumptions. One key assumption in linear (..)

DOI: 10.21307/stattrans-2019-034

MODELLING LANGUAGE EXTINCTION USING SUSCEPTIBLE-INFECTIOUS-REMOVED (SIR) MODEL

N. A. Ikoba/ E. T. Jolayemi

The study presents a stochastic epidemic model applied to the model of indigenous language extinction. The Susceptible-Infectious-Removed (SIR) categorization of an endemic disease has been reformulated to capture the dynamics of indigenous language decline, based on the assumption of nonhomogeneous mixing. The time in which an indigenous language is expected to be extinct was derived using a modified SIR model with the population segmented into several sub-communities of small sizes representin(..)

DOI: 10.21307/stattrans-2019-035

ESTIMATING POPULATION COEFFICIENT OF VARIATION USING A SINGLE AUXILIARY VARIABLE IN SIMPLE RANDOM SAMPLING

Rajesh Singh/ Madhulika Mishra

This paper proposes an improved estimation method for the population coefficient of variation, which uses information on a single auxiliary variable. The authors derived the expressions for the mean squared error of the proposed estimators up to the first order of approximation. It was demonstrated that the estimators proposed by the authors are more efficient than the existing ones. The results of the study were validated by both empirical and simulation studies.

DOI: 10.21307/stattrans-2019-036

ESTIMATION OF INCOME CHARACTERISTICS FOR REGIONS IN POLAND USING SPATIO-TEMPORAL SMALL AREA MODELS

Alina Jędrzejczak/ Jan Kubacki

The paper presents the comparison of estimation results for spatial and spatiotemporal small area models. The study was carried out for income-related variables drawn from the Polish Household Budget Survey and explanatory variables from the Polish Local Data Bank for the years 2003-2013. The properties of EBLUPs (Empirical Best Linear Unbiased Predictors) based on spatiotemporal models, which utilize spatial correlation between neighbouring areas as well as historical data, were compared and co(..)

DOI: 10.21307/stattrans-2019-037

THE IMPACT OF THE APPLIED TYPOLOGY ON THE STATISTICAL PICTURE OF POPULATION AGEING IN URBAN AREAS IN POLAND – A COMPARATIVE ANALYSIS

Tomasz Klimanek/ Sylwia Filas-Przybył

The aim of the paper is to review and compare the processes of population ageing in Polish urban areas. The study presents a novel approach to the problem, because in addition to measuring this phenomenon according to the National Official Register of the Territorial Division of the Country (TERYT) classification, it also measures population ageing according to the classification for urban areas (LAU 2 units) – Degree of Urbanisation (DEGURBA). Several traditional demographic measures for popula(..)

DOI: 10.21307/stattrans-2019-038

ON PERMUTATION LOCATION–SCALE TESTS

Dominika Polko-Zając

Statisticians are constantly looking for methods of statistical inference that would be both effective and would require meeting as few assumptions as possible. Permutation tests seem to fit here, as using them makes it possible to perform statistical inference in situations where classical parametric tests do not work. Permutation tests appear to be comparably powerful to parametric tests, but require meeting fewer assumptions, e.g. regarding the size of the sample or the from of distribution o(..)

DOI: 10.21307/stattrans-2019-039

SUBJECTIVE AND COMMUNITY WELL-BEING INTERACTION IN A MULTILEVEL SPATIAL MODELLING FRAMEWORK

Włodzimierz Okrasa/ Dominik Rozkrut

Analysing the cross-level interaction between individual and community well-being requires a joint involvement of both 'vertical' and 'horizontal' perspectives. While multilevel modelling separates the effects resulting from personal characteristics from those resulting from community features, the need to account for spatial variation and geographic membership proves that space and place matter, too. In this paper, the explicitly-spatial multilevel model has been developed to this effect, namel(..)

DOI: 10.21307/stattrans-2019-040

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