Modelling interval data with Normal and Skew-Normal distributions

• Type: Article in International Scientific Journal
• Date: 2012

Authors

brito, p (Author) FEP; silva, apd (Author) Other

Journal

Title: Journal of Applied Statistics

Vol. 39 No. 1

Pages: 3-20

ISSN: 0266-4763

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 49 Citations

ISI Web of Science

Scopus - 54 Citations

Scientific classification

FOS: Natural sciences > Mathematics

CORDIS: Physical sciences > Mathematics > Statistics

Other information

Authenticus ID: P-002-HDT

DOI: 10.1080/02664763.2011.575125

Abstract (EN): A parametric modelling for interval data is proposed, assuming a multivariate Normal or Skew-Normal distribution for the midpoints and log-ranges of the interval variables. The intrinsic nature of the interval variables leads to special structures of the variance-covariance matrix, which is represented by five different possible configurations. Maximum likelihood estimation for both models under all considered configurations is studied. The proposed modelling is then considered in the context of analysis of variance and multivariate analysis of variance testing. To access the behaviour of the proposed methodology, a simulation study is performed. The results show that, for medium or large sample sizes, tests have good power and their true significance level approaches nominal levels when the constraints assumed for the model are respected; however, for small samples, sizes close to nominal levels cannot be guaranteed. Applications to Chinese meteorological data in three different regions and to credit card usage variables for different card designations, illustrate the proposed methodology.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 18