RT Journal Article
T1 Testing equality restrictions in generalized linear models for multinomial data
A1 Pardo Llorente, María del Carmen
AB Based on φ-divergences an estimator of the generalized linear models for multinomial data under linear restrictions on the parameters is considered. New test statistics, also based on φ-divergences are considered as alternatives to the classical ones for testing a hypothesis about linear restrictions on the parameters. The asymptotic distribution of them is obtained under the null hypothesis as well as under contiguous local hypotheses. An application of the estimators and the tests is illustrated in a numerical example and in simulation studies.contiguous local hypotheses.An application of the estimators and the tests is illustratedin a numerical example and in simulation studies.
PB Springer Heidelberg
SN 0026-1335
YR 2011
FD 2011-03
LK https://hdl.handle.net/20.500.14352/42448
UL https://hdl.handle.net/20.500.14352/42448
LA eng
NO Agresti A (2002) Categorical data analysis, 2nd edn. Wiley, New York Ali SM, Silvey SD (1966) A general class of coefficients of divergence of one distribution from another. J R Stat Soc Ser B 26: 131–142 Cressie NAC, Read T (1984) Multinomial goodness-of-fit tests. J R Stat Soc B 46: 440–464 Fahrmeir L, Tutz G (2001) Multivariate statistical modelling based on generalized linear models. Springer, New York Ferguson TS (1996) A course in large sample theory. Wiley, New York Finney DJ (1971) Probit analysis, 3rd edn. Cambridge University Press, London Flemming W (1977) Functions of several variables, 2nd edn. Springer, New York Grewal RS (1952) A method for testing analgesics in mice. Br J Pharm Chemother 7: 433–437 Le Cam L (1960) Locally asymptotic normal families of distribution. University of California Publications in Statistics, Berkeley Liu I, Agresti A (2005) The analysis of ordered categorical data: an overview and a survey of recent developments. Test 14(1): 1–73Nelder JA, Wedderburn RWM (1972) Generalized linear models. J R Stat Soc A135: 370–384 Nyquist H (1991) Restricted estimation of generalized linear models. J Appl Stat 40(1): 133–141Pardo L (2006) Statistical inference based on divergence measures. Chapman & Hall, London Pardo MC (2007) ϕ  -divergence estimation in GLM for ordinal responses. Technical Report, no 67. Complutense University of Madrid Rivas MJ, Santos MT, Morales D (1995) Ré nyi test statistics for partially observed diffusion processes. J Stat Plan Inference 127: 91–102 Vajda I (1989) Theory of statistical inference and information. Kluwer Academic Publishers, Dordrecht
NO The author would like to thank a referee for critically reading this paper and making suggestions. This work was partially supported by Grants MTM2006-06872 and BSCH-UCM2008-910707.
NO Grants
NO BSCH-UCM
DS Docta Complutense
RD 3 may 2024