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A note on the difference between profile and modified profile likelihood
Biometrika, 1992The difference between profile likelihood and modified profile likelihood depends primarily on the expected value of a certain third order derivative of the log likelihood. It is shown that in exponential family problems this derivative vanishes if the parameter of interest is a mean parameter but in general not when it is a canonical parameter.
D. R. Cox, N. Reid
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On Profile Likelihood: Comment
Journal of the American Statistical Association, 2000Jianqing Fan, Wing-Hung Wong
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Adaptive Transferred-profile Likelihood Learning
2016 International Joint Conference on Neural Networks (IJCNN), 2016The recent success of representation learning is built upon the learning of relevant features, in particular from unlabelled data available in different domains. This raises the question of how to transfer and reuse such knowledge effectively so that the learning of a new task can be made easier or be improved.
Son Ngoc Tran, Artur S. d'Avila Garcez
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An approximation to the modified profile likelihood function
Biometrika, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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On a criticism of the profile likelihood function
Statistical Papers, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Montoya, José A. +2 more
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Improved profile likelihood inference
Journal of Statistical Planning and Inference, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ferrari, Silvia L. P. +2 more
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Notes on likelihood intervals and profiling
Communications in Statistics - Theory and Methods, 2000In many applications, decisions are made on the basis of function of parameters g(θ). When the value of g(theta;) is calculated using estimated values for te parameters, its is important to have a measure of the uncertainty associated with that value of g(theta;).
Shannon L. Quinn +2 more
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The likelihood of Condorcet's profiles
2002International ...
Merlin, Vincent +2 more
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Adjusted Quasi-Profile Likelihoods and Robustness
2001An adjusted quasi-profile loglikelihood for a scalar parameter of interest is discussed. The corresponding quasi-profile score has bias which is asymptotically negligible. Because of this, it is likely to provide accurate inferences with small samples or many nuisance parameters. An application to robust M-estimation is presented, which gives rise to a
R. Bellio +2 more
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On Profile Likelihood: Rejoinder
Journal of the American Statistical Association, 2000S. A. Murphy, A. W. van der Vaart
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