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  • Search: subject:"GLM for large data"
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Year of publication
Subject
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Bayesian inference 4 GLM for large data 4 Markov Chain Monte Carlo 4 Pseudo-marginal MCMC 4 estimated likelihood 4 Bayes-Statistik 2 Estimation 2 Estimation theory 2 Markov chain 2 Markov-Kette 2 Monte Carlo simulation 2 Monte-Carlo-Simulation 2 Schätztheorie 2 Schätzung 2 Sampling 1 Stichprobenerhebung 1
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Online availability
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Free 4
Type of publication
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Book / Working Paper 4
Type of publication (narrower categories)
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Working Paper 4 Arbeitspapier 2 Graue Literatur 2 Non-commercial literature 2
Language
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English 4
Author
All
Quiroz, Matias 4 Kohn, Robert 3 Villani, Mattias 3
Published in...
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Sveriges Riksbank Working Paper Series 2 Sveriges Riksbank working paper series 2
Source
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ECONIS (ZBW) 2 EconStor 2
Showing 1 - 4 of 4
Cover Image
Scalable MCMC for large data problems using data subsampling and the difference estimator
Quiroz, Matias; Villani, Mattias; Kohn, Robert - 2015
We propose a generic Markov Chain Monte Carlo (MCMC) algorithm to speed up computations for datasets with many observations. A key feature of our approach is the use of the highly efficient difference estimator from the survey sampling literature to estimate the log-likelihood accurately using...
Persistent link: https://www.econbiz.de/10011442891
Saved in:
Cover Image
Speeding up MCMC by delayed acceptance and data subsampling
Quiroz, Matias; Villani, Mattias; Kohn, Robert - 2015
We propose a generic Markov Chain Monte Carlo (MCMC) algorithm to speed up computations for datasets with many observations. A key feature of our approach is the use of the highly efficient difference estimator from the survey sampling literature to estimate the log-likelihood accurately using...
Persistent link: https://www.econbiz.de/10011442895
Saved in:
Cover Image
Speeding up MCMC by delayed acceptance and data subsampling
Quiroz, Matias - 2015
We propose a generic Markov Chain Monte Carlo (MCMC) algorithm to speed up computations for datasets with many observations. A key feature of our approach is the use of the highly efficient difference estimator from the survey sampling literature to estimate the log-likelihood accurately using...
Persistent link: https://www.econbiz.de/10011300362
Saved in:
Cover Image
Scalable MCMC for large data problems using data subsampling and the difference estimator
Quiroz, Matias; Villani, Mattias; Kohn, Robert - 2015
We propose a generic Markov Chain Monte Carlo (MCMC) algorithm to speed up computations for datasets with many observations. A key feature of our approach is the use of the highly efficient difference estimator from the survey sampling literature to estimate the log-likelihood accurately using...
Persistent link: https://www.econbiz.de/10011300365
Saved in:
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