Please use this identifier to cite or link to this item:
https://olympias.lib.uoi.gr/jspui/handle/123456789/13106Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Menendez, M. L. | en |
| dc.contributor.author | Pardo, J. A. | en |
| dc.contributor.author | Pardo, L. | en |
| dc.contributor.author | Zografos, K. | en |
| dc.date.accessioned | 2015-11-24T17:25:50Z | - |
| dc.date.available | 2015-11-24T17:25:50Z | - |
| dc.identifier.issn | 0233-1888 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/13106 | - |
| dc.rights | Default Licence | - |
| dc.subject | classification | en |
| dc.subject | discrimination | en |
| dc.subject | minimum distance classification rule | en |
| dc.subject | probabilities of misclassification | en |
| dc.subject | phi-dissimilarity | en |
| dc.subject | phi-divergence | en |
| dc.subject | discriminant-analysis | en |
| dc.subject | f-dissimilarity | en |
| dc.subject | distributions | en |
| dc.subject | affinity | en |
| dc.title | A preliminary test in classification and probabilities of misclassification | en |
| heal.type | journalArticle | - |
| heal.type.en | Journal article | en |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.identifier.primary | Doi 10.1080/02331880500097986 | - |
| heal.identifier.secondary | <Go to ISI>://000229478800001 | - |
| heal.language | en | - |
| heal.access | campus | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μαθηματικών | el |
| heal.publicationDate | 2005 | - |
| heal.abstract | Consider f(theta) to be a probability density function with parameter theta. A set of k populations can now be defined such that the ith population Pi(i) is the set of density functions f(theta 1(i)),...,f(theta mi(i)). This paper proposes a test, based on the Psi-dissimilariiy, of the hypothesis that a new individual from a population Pi(0) with a density function f(theta 0), belongs to the ith population. The probabilities of misclassification of the minimum Psi-dissimilarity classification rule are also obtained. In this paper, it is assumed that the parameters theta(1)((i)),...,theta(mi)((i)) and may be theta(0) are unknown and must be estimated from a set of training samples. Explicit expressions for the hypothesis test and the probabilities of misclassification are derived for the case where the populations Pi(i) consist of homoscedastic normal, as well as for gamma distributions. | en |
| heal.publisher | Taylor & Francis | en |
| heal.journalName | Statistics | en |
| heal.journalType | peer reviewed | - |
| heal.fullTextAvailability | TRUE | - |
| Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά). ΜΑΘ | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| zografos-2005-A preliminary test.pdf | 229.28 kB | Adobe PDF | View/Open Request a copy |
This item is licensed under a Creative Commons License
