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Bayesian partial likelihood approach for tied observations
Journal of Statistical Planning and Inference, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim, Yongdai, Kim, Dohyun
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Maximum likelihood estimation under partial sparsity constraints
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013We consider the problem of estimating two deterministic vectors in a linear Gaussian model where one of the unknown vectors is subject to a sparsity constraint. We derive the maximum likelihood estimator for this problem and develop the Projected Orthogonal Matching Pursuit (POMP) algorithm for its practical implementation.
Tirza Routtenberg +2 more
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Wiley StatsRef: Statistics Reference Online, 2018
Javier E. Flores, J. Cavanaugh
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Javier E. Flores, J. Cavanaugh
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Inefficiency of inferences with the partial likelihood
Communications in Statistics - Theory and Methods, 1986In two-sample semiparametric survival models other than the Cox proportional-hazards regression model, it is shown that partial-likelihood inference of structural parameters in the presence of fully nonpararnetric nuisance-hazards typically has relative efficiency zero compared with fuii-Iikelihood infer -ence.
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A unified partial likelihood approach for X‐chromosome association on time‐to‐event outcomes
Genetic Epidemiology, 2018Wei Xu, Meiling Hao
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Penalized partial likelihood inference of proportional hazards latent trait models
British Journal of Mathematical & Statistical Psychology, 2017Hyeon-Ah Kang
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Testing for treatment‐biomarker interaction based on local partial‐likelihood
Statistics in Medicine, 2015Yicong Liu, Wenyu Jiang, Bingshu E. Chen
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