A1 - Oesterreich, Maciej
PB - Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
N2 - The paper presents a method of detecting atypical observations in time series with or without seasonal fluctuations. Unlike classical methods of identifying outliers and influential observations, its essence consists in examining the impact of individual observations both on the fitted values of the model and the forecasts. The exemplification of theoretical considerations is the empirical example of modelling and forecasting daily sales of liquid fuels at X gas station in the period 2012-2014. As a predictor, a classic time series model was used, in which 7-day and 12-month cycle seasonality was described using dummy variables. The data for the period from 01.01.2012 to 30.06.2014 were for the estimation period and the second half of 2014 which was the period of empirical verification of forecasts. The obtained results were compared with other classical methods used to identify influential observations and outliers, i.e. standardized residuals, Cook distances and DFFIT. The calculations were carried out in the R environment and the Statistica package
L1 - http://www.dbc.wroc.pl/Content/75969/Oesterreich_On_the_method_of_identification_of_atypical_observations.pdf
L2 - http://www.dbc.wroc.pl/Content/75969
KW - forecasts
KW - identification
KW - multiple regression
KW - time series
KW - outliers
KW - prognozy
KW - identyfikacja
KW - regresja wielokrotna
KW - szeregi czasowe
KW - obserwacje odstające
ER -
T1 - On the method of identification of atypical observations in time series
UR - http://www.dbc.wroc.pl/dlibra/docmetadata?id=75969