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In the article author considers the situation in which several forecasts of the same variable are available. The forecasts was marked on basis of the causal-descriptive models for economic variable having the form of time series with seasonal fluctuations. Author creates new forecast of the same variable – the combined forecast which should be burdened with the smallest error. The author analyses...
The article was consecrated the bayesian modelling and forecasting on the ground the hierarchical models of time series in case missing data. The principles of bayesian modeling and forecasting were put-upon to analysis of production of electric power. In the article to building, estimation and prediction the bayesian, hierarchical models were used numerical methods Monte Carlo.
The following study presents the empirical analysis of the numeric methods in forecasting in conditions of lack of full information. In forecasting the following methods were used: segment, two variants of curves methods, and four variants of Lagrange methods. In analysis are used the average relative forecast errors in six variants of blanks. This study is an attempt to answer a question, whether...
The papers present analisys of econometrical modelling of the daily retail sales of liquid fuel. There were analised one petrol station of the firm which plays important role on the fuel market. The variable was described by time series hierarchical models with two types of seasonal variations: weekly variations and 12 months ones. Additionally there were included feast-days and days before and after...
The effective management of passenger traffic in the city is becoming a frequent subject of discussion for theoreticians and practitioners dealing with urban logistics. At the work an effectiveness analysis of applying various methods of forecasting described on the example of data concerning collective passenger flows in one of cities of Poland was effected. An attempt to appoint forecasts was also...
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