Application of model-selection criteria to some problems in multivariate analysis
- Stanley L. Sclove
- … show all 1 hide
Rent the article at a discountRent now
* Final gross prices may vary according to local VAT.Get Access
A review of model-selection criteria is presented, with a view toward showing their similarities. It is suggested that some problems treated by sequences of hypothesis tests may be more expeditiously treated by the application of model-selection criteria. Consideration is given to application of model-selection criteria to some problems of multivariate analysis, especially the clustering of variables, factor analysis and, more generally, describing a complex of variables.
- Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov & F. Csaki (Eds.),2nd International Symposium on Information Theory (pp. 267–281). Budapest: Akademia Kiado.
- Akaike, H. (1974). A new look at the statistical model identification.IEEE Transactions on Automatic Control, 6, 716–723.
- Akaike, H. (1981). Likelihood of a model and information criteria.Journal of Econometrics, 16, 3–14.
- Akaike, H. (1983). Statistical inference and measurement of entropy. In H. Akaike & C.-F. Wu (Eds.), Scientific inference, data analysis, and robustness (pp. 165–189). New York: Academic Press.
- Akaike, H. (1987). Factor analysis and AIC.Psychometrika, 52.
- Boekee, D. E., & Buss, H. H. (1981). Order estimation of autoregressive models.4th Aachener Kolloquium: Theorie und Anwendung der Signalverarbeitung [Proceedings of the 4th Aachen Colloquium: Theory and application of signal processing]. (pp. 126–130).
- Bozdogan, H. (1981). Multi-sample cluster analysis and approaches to validity studies in clustering individuals. Unpublished doctoral dissertation, University of Illinois at Chicago, Department of Mathematics, Chicago.
- Bozdogan, H. (1983). Determining the number of component clusters in standard multivariate normal mixture model using model-selection criteria (Technical Report UIC/DQM/A83-1, Army Research Office Contract DAAG29-82-K-0155, S. L. Sclove, Principal Investigator). Chicago: University of Illinois at Chicago.
- Bozdogan, H. (1986). Multi-sample cluster analysis as an alternative to multiple comparison procedures.Bulletin of Informatics and Cybernetics, 22 (No 1–2), 95–130.
- Bozdogan, H., & Ramirez, D. E. (1987). An expert model selection approach to determine the “best” pattern structure in factor analysis models. Unpublished manuscript.
- Bozdogan, H., & Sclove, S. L. (1984). Multi-sample cluster analysis using Akaike's information criterion.Annals of Institute Statistical Mathematics, 36, 163–180.
- Dixon, W. J., & Massey, F. J. (1969). Introduction to statistical analysis (3rd ed.). New York: McGraw-Hill.
- Kashyap, R. L. (1982). Optimal choice of AR and MA parts in autoregressive moving average models.IEEE Transactions on Pattern Analysis and Machine Intelligence, 4, 99–104.
- Rissanen, J. (1978). Modeling by shortest data description.Automatica, 14, 465–471.
- Rissanen, J. (1980). Consistent order estimates of autoregressive processes by shortest description of data. In O. L. R. Jacobs, M. H. A. Davis, M. A. H. Dempster, C. J. Harris, & P. C. Parks (Eds.),Analysis and Optimisation of Stochastic Systems (pp. 451–461). London and New York: Academic Press.
- Rissanen, J. (1983). A universal prior for integers and estimation by minimum description length.Annals of Statistics, 11, 416–431.
- Rissanen, J. (1985). Minimum-description-length principle.Encyclopedia of Statistical Sciences (Vol. 5, pp. 523–527). New York: John Wiley & Sons.
- Schwarz, G. (1978). Estimating the dimension of a model.Annals of Statistics, 6, 461–464.
- Sclove, S. L. (1983a). Application of the conditional population-mixture model to image segmentation.IEEE Transactions Pattern Analysis and Machine Intelligence, 5, 428–433.
- Sclove, S. L. (1983b). Time-series segmentation: A model and a method.Information Sciences, 29, 7–25.
- Sclove, S. L. (1984). On segmentation of time series and images in the signal detection and remote sensing contexts. In E. W. Wegman & J. G. Smith (Eds.),Statistical signal processing (pp. 421–434). New York: Marcel Dekker.
- Wolfe, J. H. (1970). Pattern clustering by multivariate mixture analysis.Multivariate Behavioral Research, 5, 329–350.
- Application of model-selection criteria to some problems in multivariate analysis
Volume 52, Issue 3 , pp 333-343
- Cover Date
- Print ISSN
- Online ISSN
- Additional Links
- model selection
- model evaluation
- Akaike's information criterion
- cluster analysis
- clustering variables
- factor analysis
- Industry Sectors
- Author Affiliations
- 1. Department of Information and Decision Sciences, College of Business Administration, University of Illinois at Chicago, Box 4348, 60680-4348, Chicago, IL