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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/124802


    Title: 時間序列模型於零售銷售預測的應用
    An application of time series models to retail sales forecasting
    Authors: 阮宣浩
    Nguyen, Xuan-Hoa
    Contributors: 莊皓鈞
    Chuang, Howard
    阮宣浩
    Nguyen, Xuan-Hoa
    Keywords: 預測
    時間序列
    模型
    訓練
    測試
    Forecasting
    Time series
    Models
    Training
    Testing
    Date: 2019
    Issue Date: 2019-08-07 16:22:02 (UTC+8)
    Abstract: Nowadays, the retail industry is very competitive. Most companies in this industry are facing many problems to satisfy customers the most and to be the most efficient. One of the most important problems is to make sales forecasting. In the past, it is more up to experiences to make sales forecasting, therefore the accuracy is often not good. With the development of computer and AI, machine learning methods, in the present, it is easier and more accurate to make a forecast for sales. In this thesis, time series models are applied with the aid of R programming to make sales forecasting. Firstly, we go to understand the basic knowledge about time series models, then we take an example of forecasting sales for a retail shop to apply these methods, including average, naive, snaive, drift, exponential smoothing, ARIMA, dynamic regression models. In the end, we come up with a conclusion about what we did in this thesis.
    Reference: Brown, R. G. (1959). Statistical forecasting for inventory control. McGraw/Hill.
    Galit Shmueli, Kenneth C.Lichtendahl Jr (2015) Practical time series forecasting with R: a hand-on guide. Axelrod Schnall Publishers.
    Holt, C. E. (1957). Forecasting seasonals and trends by exponentially weighted averages (O.N.R. Memorandum No. 52). Carnegie Institute of Technology, Pittsburgh USA.
    https://www.kaggle.com/c/favorita-grocery-sales-forecasting/overview/description
    Hyndman, R.J., & Athanasopoulos, G. (2018) Forecasting: principles and practice, 2nd edition, OTexts: Melbourne, Australia. OTexts.com/fpp2
    Wickham, H. (2016). ggplot2: Elegant graphics for data analysis (2nd ed). Springer.
    Winters, P. R. (1960). Forecasting sales by exponentially weighted moving averages. Management Science, 6, 324–342.
    Description: 碩士
    國立政治大學
    國際經營管理英語碩士學位學程(IMBA)
    106933064
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0106933064
    Data Type: thesis
    DOI: 10.6814/NCCU201900291
    Appears in Collections:[國際經營管理英語碩士學程IMBA] 學位論文

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