Comparison of Empirical Bayes and Extended Set Compound Rules for Classification of a Sequence of Crop Types

K. L. D. Gunawardena
Additional contact information
K. L. D. Gunawardena: University of Wisconsin Oshkosh, Department of Mathematics

A chapter in Computing Science and Statistics, 1992, pp 357-360 from Springer

Abstract: Abstract Hill et al. (1984) consider the application of parametric empirical Bayes theory to the classification of a sequence of crop types θ= (θ 1, θ 2,….), where each θ i = 0 or 1. The measurement vector Xi. is assumed to have density fθi (.) where both f0 and f1 are known. For fixed θ, the Xi’s are assumed to be independent. We consider the same problem, and obtain extended set compound rules for classifying the sequence of crop types.

Date: 1992
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
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:spr:sprchp:978-1-4612-2856-1_53

Ordering information: This item can be ordered from
http://www.springer.com/9781461228561

DOI: 10.1007/978-1-4612-2856-1_53

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().