A similarity-based approach to prediction

Itzhak Gilboa, Offer Lieberman and David Schmeidler

Journal of Econometrics, 2011, vol. 162, issue 1, 124-131

Abstract: Assume we are asked to predict a real-valued variable yt based on certain characteristics , and on a database consisting of for i=1,...,n. Analogical reasoning suggests to combine past observations of x and y with the current values of x to generate an assessment of y by similarity-weighted averaging. Specifically, the predicted value of y, , is the weighted average of all previously observed values yi, where the weight of yi, for every i=1,...,n, is the similarity between the vector , associated with yt, and the previously observed vector, . The "empirical similarity" approach suggests estimation of the similarity function from past data. We discuss this approach as a statistical method of prediction, study its relationship to the statistical literature, and extend it to the estimation of probabilities and of density functions.

Keywords: Density; estimation; Empirical; similarity; Kernel; Spatial; models (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4076(09)00268-1
Full text for ScienceDirect subscribers only

Related works:
Working Paper: A similarity-based approach to prediction (2011)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:162:y:2011:i:1:p:124-131

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().