A Latent Budget Analysis Approach to Classification: Examples from Economics
Latent budget analysis is a classification technique that allows clustering identification by using compositional data. This paper presents examples of how this technique deals with the unit-sum constraint by establishing an initial independence model to which subsequent models are compared in terms of their relative fitness degree. In fact, latent budget analysis does not impose linearity, homogeneity, or even specific distributions on data. Results help to understand some important relationships between capital stock composition and income or food diet composition in a heterogeneous sample of countries.
|Date of creation:||15 Sep 2005|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: https://mpra.ub.uni-muenchen.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
- Mooijaart, Ab & van der Heijden, Peter G. M. & van der Ark, L. Andries, 1999. "A least squares algorithm for a mixture model for compositional data," Computational Statistics & Data Analysis, Elsevier, vol. 30(4), pages 359-379, June.
- Juan Manuel Larrosa, 2003. "A Compositional Statistical Analysis of Capital per Worker," Macroeconomics 0301006, EconWPA.
When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:12569. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht)
If references are entirely missing, you can add them using this form.