cris.boxmetadata.label.title
New class of Johnson SB distributions and its associated regression model for rates and proportions
cris.boxmetadata.label.dateissued
01 browse.startsWith.months.july 2016
cris.boxmetadata.label.accesslevel
metadata only access
cris.boxmetadata.label.resourcetype
journal article
cris.boxmetadata.label.authors
Lemonte A.
Universidad de São Paulo
cris.boxmetadata.label.publisher
Wiley-VCH Verlag
cris.boxmetadata.label.abstract
By starting from the Johnson SB distribution pioneered by Johnson (), we propose a broad class of distributions with bounded support on the basis of the symmetric family of distributions. The new class of distributions provides a rich source of alternative distributions for analyzing univariate bounded data. A comprehensive account of the mathematical properties of the new family is provided. We briefly discuss estimation of the model parameters of the new class of distributions based on two estimation methods. Additionally, a new regression model is introduced by considering the distribution proposed in this article, which is useful for situations where the response is restricted to the standard unit interval and the regression structure involves regressors and unknown parameters. The regression model allows to model both location and dispersion effects. We define two residuals for the proposed regression model to assess departures from model assumptions as well as to detect outlying observations, and discuss some influence methods such as the local influence and generalized leverage. Finally, an application to real data is presented to show the usefulness of the new regression model.
cris.boxmetadata.label.citationstartpage
727
cris.boxmetadata.label.citationendpage
746
cris.boxmetadata.label.volume
58
cris.boxmetadata.label.issue
4
cris.boxmetadata.label.language
English
cris.boxmetadata.label.ocdeknowledgeArea
Estadísticas, Probabilidad
Matemáticas aplicadas
cris.boxmetadata.label.subjects
cris.boxmetadata.label.doi
cris.boxmetadata.label.scopusidentifier
2-s2.0-85028234328
cris.boxmetadata.label.pubmedidentifier
cris.boxmetadata.label.source
Biometrical Journal
cris.boxmetadata.label.containerissn
15214036
cris.boxmetadata.label.sponsor
The authors would like to thank the Editor, Associate Editor, and an anonymous referee for the valuable comments that have improved considerably the first version of the manuscript. Artur Lemonte gratefully acknowledges financial support from CNPq (Brazil) and FACEPE (Pernambuco, Brazil).
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