pvclass: An R Package for p Values for Classification

Zumbrunnen, Niki; Dümbgen, Lutz (2017). pvclass: An R Package for p Values for Classification. Journal of statistical software, 78(4), pp. 1-19. UCLA Statistics 10.18637/jss.v078.i04

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Let (X,Y) be a random variable consisting of an observed feature vector X and an unobserved class label Y ∈ {12,...,L} with unknown joint distribution. In addition, let D be a training data set consisting of n completely observed independent copies of (X,Y). Instead of providing point predictors (classifiers) for Y, we compute for each b ∈ {12,...,L} ap value πb (X,D) for the null hypothesis that Y=b, treating Y temporarily as a fixed parameter, i.e., we construct a prediction region for Y with a certain confidence. The advantages of this approach over more traditional ones are reviewed briefly. In principle, any reasonable classifier can be modified to yield nonparametric pvalues. We describe the R package pvclass which computes nonparametric p values for the potential class memberships of new observations as well as cross-validated pvalues for the training data. Additionally, it provides graphical displays and quantitative analyses of the p values.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Mathematics and Statistics > Institute of Mathematical Statistics and Actuarial Science

UniBE Contributor:

Zumbrunnen, Niki and Dümbgen, Lutz

Subjects:

500 Science > 510 Mathematics

ISSN:

1548-7660

Publisher:

UCLA Statistics

Language:

English

Submitter:

Lutz Dümbgen

Date Deposited:

25 Jul 2017 09:45

Last Modified:

10 Sep 2017 20:12

Publisher DOI:

10.18637/jss.v078.i04

BORIS DOI:

10.7892/boris.101172

URI:

https://boris.unibe.ch/id/eprint/101172

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