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2017 | 72 | 467-481
Article title

Predictive modeling and analysis of changes migrations in Poland

Content
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Languages of publication
EN
Abstracts
EN
The development of the research in economy has shown that conducting mathematical modeling and statistics is an effective instrument for diagnosing the progress phenomenon of socio-economic. It provides the information about the dynamics of result changeability in different periods of time. Additionally statistical analysis allows determining the prediction for periods of future and past years. Migrations is characterized by the quality of being measurable because it includes quantitative data. In recent years, demonstrate high dynamics. Conducting the analyses and calculations based on methods and statistical instruments will result in the opportunity to compare, group, analysis variables, specify trends and designate the diagnoses of achieved sports results with the implementation of the optimum vector of variables of independent variable of migrations. An analysis of the dynamics migration variability was carried out on the basis of data from the website of the main statistical office, in this article. Used the statistical methods and the testing of interdependencies. Additionally, the models of time series have been used for the sake of the analysis. The most significant aim of the analysis of the dynamics is the designation of predictions. The use of the model of time series has the task of the specification of the change of the phenomenon level in time.
Year
Volume
72
Pages
467-481
Physical description
Contributors
  • The Jerzy Kukuczka Academy of Physical Education in Katowice, 72A Mikolowska Street, 40-065 Katowice, Poland
References
  • [1] V. Assimakopoulos, K. Nikolopoulos, The theta model: a decomposition approach to forecasting. International Journal of Forecasting (2000), 16, 521-530.
  • [2] S. Brandt (Polish), Analysis of the data. Scientific Publishing PWN: Warsaw (1998).
  • [3] I. Fierla (red.) (Polish), Economic Geography. The European Union, Polish Economic Publishing: Warsaw (2007).
  • [4] J. Z. Holzer, C. Groblewska, Contemporary migrations and their research methodology. Inst. Statistics and Demography: Warsaw (1989).
  • [5] R. J. Hyndman, B. Billah, Unmasking the Theta method. International Journal of Forecasting (2003), 19, 287-290.
  • [6] R. J. Hyndman, L. K. Maxwell, I. Pitrun, B. Billah, Local linear forecasts using cubic smoothing splines. Australian & New Zealand Journal of Statistics (2005), 47(1), 87-99
  • [7] R. Iwanejko, J. Bajer (Polish), Theoretical basis of forecasting failure indicators of water supply network. Technical Journal. Environment (2012), 109 (2), 127-137
  • [8] M. Krzysztofiak, D. Urbanek (Polish), Statistical methods. Ed. 4. Scientific Publishing PWN: Warsaw (1981).
  • [9] A. Luszniewicz, T. Słaby (Polish), Statistical analysis using Statistica PL. Time series and forecasting. Scientific Publishing PWN: Warsaw (1990).
  • [10] S.G. Makridakis, M. Hibon, The M3-competition: results, conclusions and implications. International Journal of Forecasting (2000), 16, 451-476
  • [11] A. Maszczyk (Polish), Analysis and prediction of the dynamics of the volatility world’s results athletics competition in the years 1946-2011. Jerzy Kukuczka Academy of Physical Education: Katowice (2013).
  • [12] T. C. Mills, G. T. Pepper, Assesing the forecasts: an analysis of forecastingrecords of the Treasury, the London Bussiness School and the National Institute. International Journal of Forecasting (1999) 15, 247-257
  • [13] M. Nawrocka, Analysis of dynamic sports result changes in 20 km race-walking. Atletika 2014: zborník z medzinárodnej vedeckej konferencie, pp. 276-288.
  • [14] S. Osowski (Polish), Neural networks to process information. Warsaw University of Technology: Warsaw (2000).
  • [15] A. Wojna (Polish), Econometric prediction and stochastic modeling. Part 1, Technical University of Koszalin, Koszalin (2007).
  • [16] J. Żurada, M. Barski, W. Jędruch (Polish), Artificial neural networks, Scientific Publishing PWN: Warsaw (1996).
Document Type
article
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.psjd-ec33b87d-ebf5-4832-a2b1-95ed928e69f5
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