arXiv subjects

Jerzy P. Rydlewski

Publications and source records attributed to Jerzy P. Rydlewski.

6 recordsLinked to original sources

arXiv2019

Detecting a Structural Change in Functional Time Series Using Local Wilcoxon Statistic

Functional data analysis (FDA) is a part of modern multivariate statistics that analyses data providing information about curves, surfaces or anything else varying over a certain continuum. In economics and empirical finance we often have to deal with time series of functional data, where we cannot easily decide, whether they are to be considered as homogeneous or heterogeneous. At present a discussion on adequate tests of homogenity for functional data is carried. We propose a novel statistic for detetecting a structural change in functional time series based on a local Wilcoxon statistic induced by a local depth function proposed by Paindaveine and Van Bever (2013).

stat.ME↗

arXiv2019

Centrality-oriented Causality -- A Study of EU Agricultural Subsidies and Digital Developement in Poland

Results of a convincing causal statistical inference related to socio-economic phenomena are treated as especially desired background for conducting various socio-economic programs or government interventions. Unfortunately, quite often real socio-economic issues do not fulfill restrictive assumptions of procedures of causal analysis proposed in the literature. This paper indicates certain empirical challenges and conceptual opportunities related to applications of procedures of data depth concept into a process of causal inference as to socio-economic phenomena. We show, how to apply a statistical functional depths in order to indicate factual and counterfactual distributions commonly used within procedures of causal inference. Thus a modification of Rubin causality concept is proposed, i.e., a centrality-oriented causality concept. The presented framework is especially useful in a context of conducting causal inference basing on official statistics, i.e., basing on already existing databases. Methodological considerations related to extremal depth, modified band depth, Fraiman-Muniz depth, and multivariate Wilcoxon sum rank statistic are illustrated by means of example related to a study of an impact of EU direct agricultural subsidies on a digital development in Poland in a period of 2012-2019.

stat.AP↗

arXiv2018

Aggregated moving functional median in robust prediction of hierarchical functional time series - an application to forecasting web portal users behaviors

In this article, a new nonparametric and robust method of forecasting hierarchical functional time series is presented. The method is compared with Hyndman and Shang's method with respect to their unbiasedness, effectiveness, robustness, and computational complexity. Taking into account results of the analytical, simulation and empirical studies, we come to the conclusion that our proposal is superior over the proposal of Hyndman and Shang with respect to some statistical criteria and especially with respect to robustness and computational complexity. An empirical usefulness of our method is presented on example of management of a certain web portal divided into four subservices. An extensive simulation study involving hierarchical systems consisted of FAR(1) processes and Wiener processes has been conducted as well.

stat.CO↗

arXiv2018

Generalized Exponential smoothing in prediction of hierarchical time series

Shang and Hyndman (2017) proposed a grouped functional time series forecasting approach as a combination of individual forecasts obtained using generalized least squares method. We modify their methodology using generalized exponential smoothing technique for the most disaggregated functional time series in order to obtain more robust predictor. We discuss some properties of our proposals basing on results obtained via simulation studies and analysis of real data related to a prediction of a demand for electricity in Australia in 2016.

stat.ME↗

arXiv2018

New Proposals of a Stress Measure in a Capital and its Robust Estimator

In this paper a novel approach for a measurement of stresses in a capital, which induce the capital flows between economic systems, is proposed. The proposals appeal to an apparatus offered by the statistical theory of shape. We propose a stress functional basing on a concept of mean shape determined by representative particles of a capital carrier. We also propose methods of describing changes in an amount and a structure of stresses in a capital appealing, among others, to a Bookstein's pair of thin plain spline deformation, and a measure of a shape variability. We apply our approach to an indirect verification of the hypothesis according to which a capital flow between economic systems is related to an activity of an inner force related to stresses in a capital. We indicate, that the stresses create a phenomenon analogous to the heat, which may be interpreted in terms of a positive economic external effect, which attracts a capital from environment of a system to the system. For empirical studies we propose robust approach to estimate the stress functional basing on the data depth concept. In the empirical research we use data on five branch stock indexes from Warsaw Stock Exchange. The studied period involves the financial crisis of 2007.

econ.GN↗

arXiv2012

On Geometric Ergodicity of Skewed - SVCHARME models

Markov Chain Monte Carlo is repeatedly used to analyze the properties of intractable distributions in a convenient way. In this paper we derive conditions for geometric ergodicity of a general class of nonparametric stochastic volatility models with skewness driven by hidden Markov Chain with switching.

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