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Profile Maximum Likelihood Estimation of Single-Index Spatial Dynamic Panel Data Model
Mathematics, 2023 In this paper, the spatial dynamic panel data (SDPD) model is extended to the single-index spatial dynamic panel data (Si-SDPD) model by introducing a nonlinear connection function to reflect the interaction between explanatory variables.
Mengqi Zhang, Boping Tian
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Profile likelihood for identifiability analysis.
, 2023 (A) Illustrative profile likelihood as blue solid line for an identifiable parameter. For analyses of the identifiability status, the intersection with statistical threshold value (red line) at is crucial.
Bernhard Steiert (315824) +3 more
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Assessing parameter identifiability for Dynamic Causal Modelling of fMRI data
Frontiers in Neuroscience, 2015 Deterministic dynamic causal modelling (DCM) for fMRI data is a sophisticated approach to analyse effective connectivity in terms of directed interactions between brain regions of interest. To date it is difficult to know if acquired fMRI data will yield
Carolin eArand +6 more
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Multiplicative-Binomial Distribution: Some Results on Characterization, Inference and Random Data Generation [PDF]
Journal of Statistical Theory and Applications (JSTA), 2013 Multiplicative-binomial distribution is one of the distributions that allows for over-dispersion and under-dispersion relative to the standard binomial distribution.
Elsayed A.H. Elamir
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Profile likelihood function for food expenditure data.
, 2023 Profile likelihood function for food expenditure data.
Aisha Fayomi (12666894) +2 more
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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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Approximate Profile Maximum Likelihood
J. Mach. Learn. Res., 2017 We propose an efficient algorithm for approximate computation of the profile maximum likelihood (PML), a variant of maximum likelihood maximizing the probability of observing a sufficient statistic rather than the empirical sample. The PML has appealing theoretical properties, but is difficult to compute exactly.
Dmitri S. Pavlichin +2 more
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Journal of Applied Mathematics, 2022 Numerical computation of maximum likelihood estimates (MLE) is one of the most common problems encountered in applied statistics. Even if there exist many algorithms considered as performing, they can suffer in some cases for one or many of the following
Issa Cherif Geraldo
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Profile likelihood for estimation and confidence intervals [PDF]
, 2017 Normal-based confidence intervals for a parameter of interest are inaccurate when the sampling distribution of the estimate is nonnormal. The technique known as profile likelihood can produce confidence intervals with better coverage. It may be used when
Royston, Patrick
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Likelihood decision functions [PDF]
, 2012 In both classical and Bayesian approaches, statistical inference is unified and generalized by the corresponding decision theory. This is not the case for the likelihood approach to statistical inference, in spite of the manifest success of the ...
Cattaneo, Marco E. G. V.
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