Data mining on time series: An illustration using fast-food restaurant franchise data

Computational Statistics and Data Analysis

Volumn 37, Issue 4, 2001, Pages 455-476

  Liu, Lon Mu ^a   Bhattacharyya, Siddhartha ^a   Sclove, Stanley L ^a   Chen, Rong ^a   Lattyak, William J ^b  

^a UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

^b Scientific Computing Associates Corporation   (United States)

Author keywords

Automatic outlier detection; Automatic time series modeling; Expert system; Forecasting; Knowledge discovery; Outliers

Indexed keywords

DATA MINING; FORECASTING; INVENTORY CONTROL; TIME SERIES ANALYSIS;

BUSINESS OPERATION;

INFORMATION TECHNOLOGY;

FORECASTING METHOD; MODELING; TIME SERIES;

EID: 0035965494     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(01)00014-7     Document Type: Article

References (32)

1. Intervention analysis with application to economic and environmental problems
2. Estimation of time series parameters in the presence of outliers
3. An overview of data warehousing and OLAP technology
4. Joint estimation of model parameters and outlier effects in time series
5. Forecasting time series with outliers
6. Using statistics and statistical thinking to improve organisational performance
7. Editorial
8. Outliers in time series
9. Data mining and statistics: What's the connection?
10. Statistical themes and lessons for data mining
11. Data mining: Statistics and more?
12. Likelihood function of stationary multiple autoregressive moving average models
13. An integrated labor-management system for Taco bell
14. Analysis of time series with calendar effect
15. Identification of time series models in the presence of calendar variation
16. Identification of seasonal ARIMA models using a filtering method
17. A new expert system for time series modeling and forecasting
18. Recent developments of time series analysis in environmental impact studies
19. Forecasting residential consumption of natural gas using monthly and quarterly time series
20. Experiences with an automatic Box-Jenkins modeling algorithm
21. Box-Jenkins forecast model identification
22. Analysis of telephone data: A case study of forecasting seasonal time series
23. Outliers, level shifts, and variance changes in time series
24. Consistent estimates of autoregressive parameters and extended sample autocorrelation function for stationary and non-stationary ARMA models
25. Use of canonical analysis in time series model identification