Sequential likelihood ratio tests
Sture Holm (1985)
Banach Center Publications
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Sture Holm (1985)
Banach Center Publications
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Biondini, Riccardo, Lin, Yan-Xia, Mvoi, Sifa (1999)
Journal of Applied Mathematics and Decision Sciences
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Z. Govindarajulu (1985)
Banach Center Publications
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Ewa Bakinowska, Radosław Kala (2004)
Discussiones Mathematicae Probability and Statistics
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In the paper two approaches to the problem of estimation of transition probabilities are considered. The approach by McCullagh and Nelder [5], based on the independent model and the quasi-likelihood function, is compared with the approach based on the marginal model and the standard likelihood function. The estimates following from these two approaches are illustrated on a simple example which was used by McCullagh and Nelder.
David R. Cox (1983)
Qüestiió
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A review is given of recent work on asymptotic theory leading to a recommendation to use ratio likelihood rests with, where available, a Bartlett adjustment factor.
Tzavidis, Nikos, Lin, Yan-Xia (2006)
Journal of Applied Mathematics and Decision Sciences
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Rippon, Paul, Rayner, J.C.W. (2010)
Advances in Decision Sciences
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Baklizi, Ayman, Daud, Isa, Ibrahim, Noor Akma (1999)
Bulletin of the Malaysian Mathematical Society. Second Series
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Jean-Marc Azaïs, Élisabeth Gassiat, Cécile Mercadier (2009)
ESAIM: Probability and Statistics
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This paper deals with the likelihood ratio test (LRT) for testing hypotheses on the mixing measure in mixture models with or without structural parameter. The main result gives the asymptotic distribution of the LRT statistics under some conditions that are proved to be almost necessary. A detailed solution is given for two testing problems: the test of a single distribution against any mixture, with application to Gaussian, Poisson and binomial distributions; the test of the number...
C. Radhakrishna Rao (1962)
Annales scientifiques de l'Université de Clermont. Mathématiques
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Haiyan Xuan, Lixin Song, Muhammad Amin, Yongxia Shi (2017)
Open Mathematics
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This paper studies the quasi-maximum likelihood estimator (QMLE) for the generalized autoregressive conditional heteroscedastic (GARCH) model based on the Laplace (1,1) residuals. The QMLE is proposed to the parameter vector of the GARCH model with the Laplace (1,1) firstly. Under some certain conditions, the strong consistency and asymptotic normality of QMLE are then established. In what follows, a real example with Laplace and normal distribution is analyzed to evaluate the performance...