Inter Time Series Sales Forecasting

2013/03/01 by Manisha Gahirwal, Gahirwal, Manisha
Computer Science · Decision Sciences · #Applications (stat.AP) #FOS: Computer and information sciences #Forecasting Techniques and Applications #Stock Market Forecasting Methods #Time Series Analysis and Forecasting

paper · pdf · doi:10.48550/arxiv.1303.0117

openalex publication_date 2013/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Combining forecast from different models has shown to perform better than single forecast in most time series. To improve the quality of forecast we can go for combining forecast. We study the effect of decomposing a series into multiple components and performing forecasts on each component separately... The original series is decomposed into trend, seasonality and an irregular component for each series. The statistical methods such as ARIMA, Holt-Winter have been used to forecast these components. In this paper we focus on how the best models of one series can be applied to similar frequency pattern series for forecasting using association mining. The proposed method forecast values has been compared with Holt Winter method and shown that the results are better than Holt Winter method

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