利用貝式方法預測和估計在某時期的顧客行為｜國立中央大學博碩士論文系統

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研究生：	吳佩琪 Pei-chi Wu
論文名稱：	利用貝式方法預測和估計在某時期的顧客行為 A Bayesian Approach to the Prediction and Estimation for Period-to-Period Customer Behavior.
指導教授：	葉英傑 Ying-chieh Yeh
口試委員:
學位類別：	碩士 Master
系所名稱：	管理學院 - 工業管理研究所 Graduate Institute of Industrial Management
畢業學年度：	97
語文別：	英文
論文頁數：	25
中文關鍵詞：	負二項模型、階層貝式方法
外文關鍵詞：	Hierarchical Bayes, NBD Model
相關次數：	點閱：19 下載：0
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在本篇文章主要估計和預測在特定的時間中顧客的購買行為。1959年，Ehrenberg根據顧客的購買情況服從Poisson分配；購買率服從Gamma分配時，他提出了NBD模型。然而前一期購買量為零時，NBD模型預測結果會有誤差，因此我們針對這特殊的情況提出改善，增加hard core nonbuyers當作先前參數，服從Beta分配，使用階層貝式方法發展出新的模型。此外，我們用利更簡單和更公平的方法做參數估計。最後，使用MATLAB做數值模擬並分別做預測結果的比較。

In this study, a novel statistic model for predicting and estimating for period-to-period customer behavior has been constructed. By use of combining hard core nonbuyers, α, as a prior parameter with hierarchical Bayes procedure. The NBD model has been developed to more precise under the zero class condition. We do numerical simulation by running computer program, MATLAB and compare the results of the NBD model with our model by empirical examples. In terms of mean absolute deviation, the generated model could diminish bias in some situations.

摘要 ............................................................................................................................Ⅰ
Abstract .......................................................................................................................Ⅱ
Table of Content...........................................................................................................Ⅲ
List of Figures..............................................................................................................Ⅳ
List of Tables..................................................................................................................V
Introduction.................................................................................................................1
1 Motivation and Background.............................................................................1
2 Thesis Framework............................................................................................2
Literature review.........................................................................................................5
1 Bayesian Forecasting........................................................................................5
2 Hierarchical Bayesian.......................................................................................5
3 Consumer Purchasing Patterns.........................................................................6
The model....................................................................................................................7
1 Model Assumption...........................................................................................7
2 NBD Model......................................................................................................7
3 The Zero Class and Hard Core Nonbuyers Problems......................................8
4 Beta-Binomial Model.......................................................................................9
5 Parameters of Estimation...............................................................................12
Numerical Analysis ..................................................................................................15
1 Description of Simulate Examples.................................................................15
2 Comparison of Prediction...............................................................................18
Conclusion and future research.................................................................................24
1 Conclusion......................................................................................................24
2 Future research...............................................................................................24
Reference..................................................................................................................... 25

                                

[1] Anscombe, F J (1950), "Sampling Theory of the Negative Binomial and Logarithmic Distributions," Biometrika, 37, 358-382.
[2] Goodhardt, G. J., and Ehrenberg, A. S. C.(1967), "Conditional Trend Analysis: A Breakdown by Initial Purchasing Level," Journal of Marketing Research, 4, 155-162
[3] Donald G. Morrison, "Analysis of Consumer Purchase Data: A Bayesian Approach," Industrial Management Review, 9 (Winter 1968), 31-40.
[4] Donald G. Morrison, "Conditional Trend-Analysis: A Model that Allows for Nonusers," Journal of Marketing Research, 6 (August 1969), 342-6.
[5] A. S. C EHRENBERG*(1970)” Note on Never-Buyers” Journal of Marketing Research, Vol. VII (November 1970), 536-8
[6] Goodhardt, G. J., Ehrenberg, A. S. C., and Chatfield, C.(1984), "The Dirichlet: A Comprehensive Model of Buying Behavior.”
[7] Schmittlein, D. C., and Morrison, D. G.(1983), "Prediction of Future Random Events With the Condensed Negative Binomial Distribution," Journal of the American Statistical Association, 78, 449- 456
[8] Robbins, H.(1977), "Prediction and Estimation for the Compound Poisson Distribution,"Proceedings of the Academy of Sciences, U.S.A., 74,2067-2071.
[9] Donald G. Morrison and David C. Schmittlein. (1988),” Generalizing the NBD Model for Customer Purchases: What Are the Implications and Is It Worth the Effort?” Journal of Business & Economic Statistics, April 1988
[10] John W. Bradford and Paulk. Sugrue(1990), “A Bayesian Approach to the Two-period Style-goods Inventory Problem with Single Replenishment and Heterogeneous Poisson Demands” The Journal of the Operational Research Society, Vol. 41, No. 3 (Mar., 1990), pp. 211- 218

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