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A profile likelihood approach for longitudinal data analysis
Biometrics, 2018 SummaryInappropriate choice of working correlation structure in generalized estimating equations (GEE) could lead to inefficient parameter estimation while impractical normality assumption in likelihood approach would limit its applicability in longitudinal data analysis. In this article, we propose a profile likelihood method for estimating parameters
Ziqi Chen, M. Tang, Wei Gao
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Journal of the American Statistical Association, 2000
Abstract We show that semiparametric profile likelihoods, where the nuisance parameter has been profiled out, behave like ordinary likelihoods in that they have a quadratic expansion. In this expansion the score function and the Fisher information are replaced by the efficient score function and efficient Fisher information.
Murphy, S.A., van der Vaart, A.W.
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Abstract We show that semiparametric profile likelihoods, where the nuisance parameter has been profiled out, behave like ordinary likelihoods in that they have a quadratic expansion. In this expansion the score function and the Fisher information are replaced by the efficient score function and efficient Fisher information.
Murphy, S.A., van der Vaart, A.W.
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Adjustments to profile likelihood
Biometrika, 1989Summary: Conditional and marginal likelihoods constructed from parameter-dependent functions of the data have an additional parameter dependence that changes with the choice of supporting metric for the corresponding densities. We consider constructing marginal and conditional likelihoods by using densities expressed in terms of an intrinsic choice of ...
Fraser, D. A. S., Reid, N.
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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.
S. Tran, A. Garcez
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Statistics & Probability Letters, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lin, Lu, Zhang, Runchu
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lin, Lu, Zhang, Runchu
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Model-Averaged Profile Likelihood Intervals
Journal of Agricultural, Biological, and Environmental Statistics, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fletcher, David, Turek, Daniel
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Profile likelihood in systems biology
The FEBS Journal, 2013Inferring knowledge about biological processes by a mathematical description is a major characteristic of Systems Biology. To understand and predict system's behavior the available experimental information is translated into a mathematical model.
Kreutz, Clemens +3 more
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