Results 261 to 270 of about 2,583,946 (296)

Model-Averaged Profile Likelihood Intervals

Journal of Agricultural, Biological, and Environmental Statistics, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fletcher, David, Turek, Daniel
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Improved profile likelihood inference

Journal of Statistical Planning and Inference, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ferrari, Silvia L. P., Lucambio, Fernando, Cribari-Neto, Francisco   +2 more
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Notes on likelihood intervals and profiling

Communications in Statistics - Theory and Methods, 2000
In 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, Thomas J. Harris, David W. Bacon   +2 more
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On a criticism of the profile likelihood function

Statistical Papers, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Montoya, José A., Díaz-Francés, Eloísa, Sprott, David A.   +2 more
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An approximation to the modified profile likelihood function

Biometrika, 1998
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The likelihood of Condorcet's profiles

2002
International ...
Merlin, Vincent, Valognes, Fabrice, Tataru, M.   +2 more
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Adjusted Quasi-Profile Likelihoods and Robustness

2001
An 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, BRAZZALE, ALESSANDRA ROSALBA, VENTURA, LAURA   +2 more
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On Profile Likelihood: Rejoinder

Journal of the American Statistical Association, 2000
S. A. Murphy, A. W. van der Vaart
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The modified profile likelihood function

2000
Abstract In Chapter 8 it was shown that, in some cases, inference about a parameter of interest ψ may be based on a marginal or conditional likelihood function. Those methods are only available however when the model has a particular structure.
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Profile-profile methods provide improved fold-recognition: A study of different profile-profile alignment methods

Proteins: Structure, Function and Bioinformatics, 2004
Björn Wallner, Arne Elofsson
exaly