Aviso: para depositar documentos, por favor, inicia sesión e identifícate con tu cuenta de correo institucional de la UCM con el botón MI CUENTA UCM. No emplees la opción AUTENTICACIÓN CON CONTRASEÑA
 

Wald type and phi-divergence based test-statistics for isotonic binomial proportions.

dc.contributor.authorMartin, N.
dc.contributor.authorMata, R.
dc.contributor.authorPardo Llorente, Leandro
dc.date.accessioned2023-06-18T06:48:52Z
dc.date.available2023-06-18T06:48:52Z
dc.date.issued2016
dc.description.abstractIn this paper new test statistics are introduced and studied for the important problem of testing hypothesis that involves inequality constraint on proportions when the sample comes from independent binomial random variables: Wald type and phi-divergence based test-statistics. As a particular case of phi-divergence based test-statistics, the classical likelihood ratio test is considered. An illustrative example is given and the performance of all of them for small and moderate sample sizes is analyzed in an extensive simulation study. (C) 2015 International Association for Mathematics and Computers in Simulation
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.sponsorshipSpanish Grant
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/34979
dc.identifier.doi10.1016/j.matcom.2015.06.008
dc.identifier.issn0378-4754
dc.identifier.officialurlhttp://www.sciencedirect.com/science/article/pii/S0378475415001275
dc.identifier.relatedurlhttp://www.sciencedirect.com
dc.identifier.urihttps://hdl.handle.net/20.500.14352/24279
dc.journal.titleMathematics and computers in simulation
dc.language.isoeng
dc.page.final49
dc.page.initial31
dc.publisherElsevier
dc.relation.projectIDMTM-2012-33740
dc.rights.accessRightsrestricted access
dc.subject.cdu519.22
dc.subject.keywordWald-type statistics
dc.subject.keywordPhi-divergence statistics
dc.subject.keywordInequality constrains
dc.subject.keywordLoglinear model
dc.subject.keywordLogistic regression
dc.subject.ucmEstadística matemática (Matemáticas)
dc.subject.unesco1209 Estadística
dc.titleWald type and phi-divergence based test-statistics for isotonic binomial proportions.
dc.typejournal article
dc.volume.number120
dcterms.references[1] R.E. Barlow, D. Bartholomew, J.M. Bremner, H.D. Brunk, Statistical Inference under Order Restrictions: The Theory and Application of Isotonic Regression, Wiley, New York,1972. [2] D.J. Bartholomew, A test of homogeneity for ordered alternatives, Biometrika 46 (1959) 36–48. [3] M.W. Browne, Asymptotically distribution-free methods for the analysis of covariance structures, Br. J. Math. Stat. Psychol. 37 (1984) 62–83. [4] R. Colombi, A. Forcina, Marginal regression models for the analysis of positive association of ordinal response variables, Biometrika 88 (2001) 1007–1019. [5] J.R. Dale, Asymptotic normality of goodness-of-fit statistics for sparse product multinomials, J. R. Stat. Soc. Series B Stat. Methodol. 48 (1986) 48–59. [6] V. Dardanoni, A. Forcina, A unified approach to likelihood inference on stochastic orderings in a nonparametric context, J. Amer. Statist.Assoc. 93 (1998) 1112–1122. [7] J.L. Fleiss, B. Levin, M.C. Paik, Statistical Methods for Rates and Proportions, third ed., Wiley, New York, 2003. [8] B.I. Graubard, E.L. Korn, Choice of column scores for testing independence in ordered 2 × I contingency tables, Biometrics 43 (1987)471–476. [9] A. Kudo, A multivariate analogue of the one-sided test, Biometrika 50 (1963) 403–418. [10] J.Y. Mancuso, H. Ahan, J.J. Chen, Order-restricted dose-related trend tests, Stat. Med. 20 (2001) 2305–2318. [11] N. Martin, N. Balakrishnan, Hypothesis testing in a generic nesting framework for general distributions, J. Multivariate Anal. 118 (2013) 1–23. [12] N. Martin, R. Mata, L. Pardo, Phi-divergence statistics for the likelihood ratio order: an approach based on log-linear models, J. Multivariate Anal. 130 (2014) 387–408. [13] M.L. Menendez, D. Morales, L. Pardo, Tests based on divergences for and against ordered alternatives in cubic contingency tables, Appl. Math. Comput. 134 (2003) 207–213. [14] L. Pardo, Statistical Inference Based on Divergence Measures, Chapman & Hall/CRC, Boca Raton, 2006. [15] T.R.C. Read, N.A.C. Cressie, Goodness of Fit Statistics for Discrete Multivariate Data, Springer-Verlag, New York,1989. [16] T. Robertson, F.T. Wright, R. Dykstra, Order Restricted Statistical Inference, John Wiley and Sons, New York, 1988. [17] P.K. Sen, M.J. Silvapulle, An appraisal of some aspects of statistical inference under inequality constraints, J. Statist. Plann. Inference 107 (2002) 3–43. [18] A. Shapiro, Asymptotic distribution of test statistics in the analysis of moment structures underinequality constraints, Biometrika 72 (1985)133–144. [19] A. Shapiro, Towards a unified theory of inequality constrained testing in multivariate analysis, Int. Stat. Rev. 56 (1988) 49–62. [20] M.J. Silvapulle, P.K. Sen, Constrained Statistical Inference: Inequality, Order, and Shape Restrictions, Wiley, New York, 2005
dspace.entity.typePublication
relation.isAuthorOfPublicationa6409cba-03ce-4c3b-af08-e673b7b2bf58
relation.isAuthorOfPublication.latestForDiscoverya6409cba-03ce-4c3b-af08-e673b7b2bf58

Download

Original bundle

Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
PardoLlorente105 libre.pdf
Size:
710.43 KB
Format:
Adobe Portable Document Format
Loading...
Thumbnail Image
Name:
PardoLlorente105.pdf
Size:
1.61 MB
Format:
Adobe Portable Document Format

Collections