Title:

On the method of identification of atypical observations in time series

Group publication title:

Ekonometria = Econometrics

Title in english:

O metodzie identyfikacji obserwacji nietypowych w szeregach czasowych

Creator:

Oesterreich, Maciej

Subject and Keywords:

forecasts ; identification ; multiple regression ; time series ; outliers ; prognozy ; identyfikacja ; regresja wielokrotna ; szeregi czasowe ; obserwacje odstające

Description:

Econometrics = Ekonometria, 2020, Vol. 24, No. 2, s. 1-16

Abstrakt:

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

Publisher:

Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu

Place of publication:

Wrocław

Date:

2020

Resource Type:

artykuł

Resource Identifier:

doi:10.15611/eada.2020.2.01

Language:

eng

Relation:

Econometrics = Ekonometria, 2020, Vol. 24, No. 2

Rights:

Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy

Access Rights:

Dla wszystkich zgodnie z licencją

License:

CC BY-NC-ND 3.0 PL

Location:

Uniwersytet Ekonomiczny we Wrocławiu