Results 31 to 40 of about 57,825 (288)
Approximate Bayesian Computation by Modelling Summary Statistics in a Quasi-likelihood Framework [PDF]
, 2015 Approximate Bayesian Computation (ABC) is a useful class of methods for Bayesian inference when the likelihood function is computationally intractable. In practice, the basic ABC algorithm may be inefficient in the presence of discrepancy between prior ...
Cabras, Stefano +2 more
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Nonparametric quasi-likelihood
The Annals of Statistics, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chiou, Jeng-Min, Müller, Hans-Georg
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How to use χ2 test correctly——the likelihood ratio test and the implementation of SAS software
Sichuan jingshen weisheng, 2021 The purpose of this article was to introduce the likelihood ratio test and the SAS implementation. Specifically， three definitions of the likelihood ratio test statistics and six more commonly used likelihood ratio test statistics were introduced.
Hu Chunyan, Hu Liangping
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E-Jurnal Matematika, 2013 Poisson regression can be used to analyze count data, with assuming equidispersion. However, in the case of overdispersion often occur in the count data.
DESAK PUTU PRAMI MEITRIANI +2 more
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Quasi-likelihood and Optimal Estimation [PDF]
, 2010 Let \(\Theta\) be an open subset of \(R^ p\) and let \({\mathcal P}=\{{\mathcal P}_{\theta}\}\) be a union of parametric families of probability measures, each family being indexed by the same parameter \(\theta\in \Theta\). Let \(\{X_ t:\) \(0\leq t\leq T\}\) be a sample in discrete or continuous time which is drawn from some process taking values in \
Godambe, V. P., Heyde, C. C.
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Mean square convergence rates for maximum quasi-likelihood estimators [PDF]
, 2014 In this note we study the behavior of maximum quasilikelihood estimators (MQLEs) for a class of statistical models, in which only knowledge about the first two moments of the response variable is assumed.
Boer, Arnoud V. den, Zwart, Bert
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Restricted Empirical Likelihood Estimation for Time Series Autoregressive Models
Journal of Statistical Theory and Applications (JSTA), 2021 In this paper, we first illustrate the restricted empirical likelihood function, as an alternative to the usual empirical likelihood. Then, we use this quasi-empirical likelihood function as a basis for Bayesian analysis of AR(r) time series models.
Mahdieh Bayati +2 more
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Modeling gene expression measurement error: a quasi-likelihood approach
BMC Bioinformatics, 2003 Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known.
Strimmer Korbinian
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Local Influence Analysis for Quasi-Likelihood Nonlinear Models with Random Effects
Journal of Probability and Statistics, 2018 We propose a quasi-likelihood nonlinear model with random effects, which is a hybrid extension of quasi-likelihood nonlinear models and generalized linear mixed models. It includes a wide class of existing models as examples.
Tian Xia, Jiancheng Jiang, Xuejun Jiang
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The Annals of Statistics, 1983 The connection between quasi-likelihood functions, exponential family models and nonlinear weighted least squares is examined. Consistency and asymptotic normality of the parameter estimates are discussed under second moment assumptions. The parameter estimates are shown to satisfy a property of asymptotic optimality similar in spirit to, but more ...
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