Výsledky vyhľadávania - "Marginal likelihood"

Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo

Autori: Karamanis, Minas Seljak, Uroš

Zdroj: Statistics and Computing. 35(5)

Predmety: 49 Mathematical Sciences (for-2020), 4905 Statistics (for-2020), 1.4 Methodologies and measurements (hrcs-rac), Generic health relevance (hrcs-hc), Sequential Monte Carlo, Importance sampling, Marginal likelihood, Bayesian inference, 0104 Statistics (for), 0802 Computation Theory and Mathematics (for), Statistics & Probability (science-metrix), 4901 Applied mathematics (for-2020), 4903 Numerical and computational mathematics (for-2020), 4905 Statistics (for-2020)

Popis súboru: application/pdf

Prístupová URL adresa: https://escholarship.org/uc/item/5qc8f2mx
https://escholarship.org/content/qt5qc8f2mx/qt5qc8f2mx.pdf

Whittaker–Henderson smoothing revisited: A modern statistical framework for practical use

Autori: Biessy, Guillaume

Prispievatelia: Biessy, Guillaume

Zdroj: ASTIN Bulletin. :1-31

Predmety: duration models, [STAT.ME] Statistics [stat]/Methodology [stat.ME], extrapolation, marginal likelihood, experience tables, approche bayésienne empirique, modèles additifs généralisés, generalized additive models, smoothing methods, maximum de vraisemblance, méthodes de lissage, tables d'expérience, empirical Bayes approach, vraisemblance marginale, modèles de durée, maximum likelihood

Popis súboru: application/pdf

Prístupová URL adresa: https://hal.science/hal-04124043v5/document
https://hal.science/hal-04124043v5
https://doi.org/10.1017/asb.2025.10061

Statistical Finite Elements via Interacting Particle Langevin Dynamics

Autori: Glyn-Davies, Alex Duffin, Connor Kazlauskaite, Ieva a ďalší

Zdroj: SIAM/ASA Journal on Uncertainty Quantification. 13:1200-1227

Predmety: AAM requested, FOS: Computer and information sciences, statistical finite elements, inverse problems, maximum marginal likelihood estimation, FOS: Physical sciences, Computational Physics (physics.comp-ph), Statistics - Computation, Physics - Computational Physics, Langevin dynamics, Computation (stat.CO)

Prístupová URL adresa: http://arxiv.org/abs/2409.07101
http://eprints.lse.ac.uk/129337/

Interacting particle Langevin algorithm for maximum marginal likelihood estimation

Autori: Akyildiz, OD Crucinio, FR Girolami, M a ďalší

Prispievatelia: Akyildiz, OD Crucinio, FR Girolami, M a ďalší

Zdroj: ESAIM: Probability and Statistics. 29:243-280

Predmety: FOS: Computer and information sciences, Maximum marginal likelihood, Statistics - Machine Learning, Probability (math.PR), FOS: Mathematics, interacting particles, Machine Learning (stat.ML), simulated annealing, optimisation via sampling, EM algorithm, Statistics - Computation, Mathematics - Probability, Computation (stat.CO)

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/abs/2303.13429

A Bayesian-Inspired Approach to Passive Radar Detection

Autori: Ramírez García, David Míguez Arenas, Joaquín Santamaría Caballero, Ignacio a ďalší

Prispievatelia: Ramírez García, David Míguez Arenas, Joaquín Santamaría Caballero, Ignacio a ďalší

Zdroj: e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)

Predmety: Complex inverse-wishart distribution, Telecomunicaciones, Multi-sensor array, Marginal likelihood ratio, Coherence, Passive radar

Popis súboru: application/pdf

Prístupová URL adresa: https://hdl.handle.net/10016/47021

A subsampling approach for Bayesian model selection

Autori: Lachmann, Jon Storvik, Geir Frommlet, Florian a ďalší

Zdroj: International Journal of Approximate Reasoning. 151:33-63

Predmety: Bayesian model averaging, Bayesian model selection, MCMC, Subsampling, Tall data, Bayesian networks, Iterative methods, Laplace transforms, Markov processes, Monte Carlo methods, Optimization, Stochastic models, Stochastic systems, Bayesian version, Computational burden, Laplace's approximation, Marginal likelihood, Markov chain Monte Carlo, Markov Chain Monte-Carlo, Large dataset

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-211691
https://doi.org/10.1016/j.ijar.2022.08.018

Infinite Mixture Models for Improved Modeling of Across-Site Evolutionary Variation

Autori: Mandev S Gill Guy Baele Marc A Suchard a ďalší

Zdroj: Molecular Biology and Evolution. 42

Predmety: FOS: Computer and information sciences, Biochemistry & Molecular Biology, model selection, 3101 Biochemistry and cell biology, across-site variation, CHAIN MONTE-CARLO, LIKELIHOOD-ESTIMATION, Bayesian statistics, 0601 Biochemistry and Cell Biology, 3105 Genetics, Bayesian nonparametrics, Evolution, Molecular, Methodology (stat.ME), SAMPLING METHODS, substitution models, NUCLEOTIDE SUBSTITUTIONS, 0603 Evolutionary Biology, INFORMATION CRITERIA, MARGINAL LIKELIHOOD, Quantitative Biology - Populations and Evolution, Phylogeny, 3104 Evolutionary biology, Statistics - Methodology, Genetics & Heredity, virus evolution, Evolutionary Biology, 0604 Genetics, Science & Technology, Models, Genetic, MOLECULAR CLOCK, REAL-TIME, Populations and Evolution (q-bio.PE), Bayes Theorem, DNA-SEQUENCES, Markov Chains, phylogenetics, FOS: Biological sciences, BAYES FACTORS, Life Sciences & Biomedicine

Prístupová URL adresa: http://arxiv.org/abs/2412.06042
https://lirias.kuleuven.be/handle/20.500.12942/772486
https://doi.org/10.1093/molbev/msaf199

Bayesian predictive distributions of oil returns using mixed data sampling volatility models

Autori: Virbickaitė, Audronė Nguyen, Hoang Tran, Minh-Ngoc

Zdroj: Resources policy. 86

Predmety: ES, GARCH, GAS, Log marginal likelihood, MIDAS, SV, VaR

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-198443
https://liu.diva-portal.org/smash/get/diva2:1804462/FULLTEXT01.pdf

Nudging state-space models for Bayesian filtering under misspecified dynamics

Autori: González Hernández, Omar Fabián Akyildiz, Omer Deniz Crisan, Dan a ďalší

Prispievatelia: González Hernández, Omar Fabián Akyildiz, Omer Deniz Crisan, Dan a ďalší

Zdroj: e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)

Predmety: FOS: Computer and information sciences, Telecomunicaciones, Marginal likelihood, Probability (math.PR), Model mismatch, FOS: Mathematics, Misspecified dynamics, Bayesian filter, Statistics - Computation, Mathematics - Probability, Computation (stat.CO), Nudging

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/abs/2411.00218
https://hdl.handle.net/10016/47783

Empirical Bayes methods in high dimensions: a survey and ongoing debates

Autori: Rizzelli, Stefano

Zdroj: METRON.

Predmety: Adaptive posterior distributions, Gaussian process, High-dimensional analysis, Marginal likelihood, Sparse sequence model

Prístupová URL adresa: https://hdl.handle.net/11577/3555151
https://doi.org/10.1007/s40300-025-00293-y

Importance sampling and Bayesian model comparison in ecology and evolution

Autori: Dave W. Hudson Dave J. Hodgson Michael A. Cant a ďalší

Zdroj: Methods in Ecology and Evolution, Vol 14, Iss 12, Pp 2994-3006 (2023)

Predmety: 0301 basic medicine, Ecology, Evolution, Bayesian, 01 natural sciences, model-comparison, multimodel inference, survival analysis, model‐comparison, 03 medical and health sciences, importance sampling, QH359-425, marginal-likelihood estimation, marginal‐likelihood estimation, 0101 mathematics, QH540-549.5

Prístupová URL adresa: https://doaj.org/article/e77a6d767d16451e825c0fa36e82567c

Efficient selection between hierarchical cognitive models: Cross-validation with variational Bayes

Autori: Viet Hung Dao David Gunawan Minh-Ngoc Tran a ďalší

Prispievatelia: Viet Hung Dao David Gunawan Minh-Ngoc Tran a ďalší

Zdroj: Psychological Methods. 29:219-241

Predmety: FOS: Computer and information sciences, 05 social sciences, Bayes Theorem, marginal likelihood, Models, Psychological, algorithms, Statistics - Applications, Cognition, Research Design, Humans, Applications (stat.AP), 0501 psychology and cognitive sciences, model screening, LBA model, Algorithms

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/35446049
http://arxiv.org/abs/2102.06814

Improved marginal likelihood estimation via power posteriors and importance sampling

Autori: LI, Yong WANG, Nianling Jun YU

Zdroj: Journal of Econometrics. 234:28-52

Predmety: Importance sampling, 05 social sciences, power posteriors, marginal likelihood, 01 natural sciences, Bayes factor, Markov chain Monte Carlo, importance sampling, model choice, Marginal likelihood, 0502 economics and business, Markov Chain Monte Carlo, Econometrics, Power posteriors, 0101 mathematics, Model choice

Popis súboru: application/pdf

Prístupová URL adresa: https://ink.library.smu.edu.sg/soe_research/2552

On the Use of the Harmonic Mean Estimator for Selecting the Hypothetical Income Distribution from Grouped Data

Autori: Kazuhiko Kakamu

Zdroj: Journal of Risk and Financial Management ; Volume 18 ; Issue 2 ; Pages: 72

Predmety: harmonic mean estimator, hypothetical income distribution, Metropolis–Hastings algorithm, marginal likelihood, Markov chain Monte Carlo (MCMC) method

Popis súboru: application/pdf

Relation: Mathematics and Finance; https://dx.doi.org/10.3390/jrfm18020072

Dostupnosť: https://doi.org/10.3390/jrfm18020072

Easily Computed Marginal Likelihoods for Multivariate Mixture Models Using the THAMES Estimator

Autori: Metodiev, Martin Irons, Nicholas, J Perrot-Dockès, Marie a ďalší

Prispievatelia: Metodiev, Martin Irons, Nicholas, J Perrot-Dockès, Marie a ďalší

Zdroj: https://hal.science/hal-05053852 ; 2025.

Predmety: harmonic mean estimator, label switching, marginal likelihood estimation, mixture modelling, Bayesian statistics, [STAT.ME]Statistics [stat]/Methodology [stat.ME]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2504.21812; ARXIV: 2504.21812

Dostupnosť: https://hal.science/hal-05053852
https://hal.science/hal-05053852v2/document
https://hal.science/hal-05053852v2/file/arxiv.pdf

Revisiting Whittaker-Henderson Smoothing ; Une vision moderne du lissage de Whittaker-Henderson

Autori: Biessy, Guillaume Laboratoire de Probabilités, Statistique et Modélisation (LPSM (UMR_8001)) Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)

Prispievatelia: Biessy, Guillaume Laboratoire de Probabilités, Statistique et Modélisation (LPSM (UMR_8001)) Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)

Zdroj: https://hal.science/hal-04124043 ; 2025.

Predmety: maximum likelihood, generalized additive models, empirical Bayes approach, marginal likelihood, extrapolation, smoothing methods, duration models, experience tables, méthodes de lissage, modèles de durée, tables d'expérience, maximum de vraisemblance, modèles additifs généralisés, approche bayésienne empirique, vraisemblance marginale, JEL: C - Mathematical and Quantitative Methods/C.C1 - Econometric and Statistical Methods and Methodology: General/C.C1.C14 - Semiparametric and Nonparametric Methods: General, JEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C24 - Truncated and Censored Models • Switching Regression Models • Threshold Regression Models, JEL: C - Mathematical and Quantitative Methods/C.C5 - Econometric Modeling/C.C5.C51 - Model Construction and Estimation, [STAT.ME]Statistics [stat]/Methodology [stat.ME]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2306.06932; ARXIV: 2306.06932

Dostupnosť: https://hal.science/hal-04124043
https://hal.science/hal-04124043v4/document
https://hal.science/hal-04124043v4/file/Whitaker_Henderson_7_with_appendix.pdf

Left-truncated health insurance claims data: theoretical review and empirical application

Autori: Rafael Weißbach Achim Dörre Dominik Wied a ďalší

Zdroj: Advances in statistical analysis 108, 31-68 (2024). doi:10.1007/s10182-023-00471-1

Predmety: ddc:510, FOS: Computer and information sciences, Sample selection, Left truncation, 01 natural sciences, 3. Good health, Methodology (stat.ME), Marginal likelihood, 62N99, Conditional likelihood, Dementia, 0101 mathematics, Statistics - Methodology

Prístupová URL adresa: http://arxiv.org/abs/2103.05262
https://hdl.handle.net/10419/312276
https://hdl.handle.net/10419/318000

Marginal Likelihood Computation for Model Selection and Hypothesis Testing: An Extensive Review

Autori: F. Llorente L. Martino D. Delgado a ďalší

Prispievatelia: F. Llorente L. Martino D. Delgado a ďalší

Zdroj: e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)

Predmety: FOS: Computer and information sciences, Doubly intractable posteriors, Computer Science - Machine Learning, Bayesian evidence, Partition functions, Estadística, 02 engineering and technology, Quadrature rules, Model selection, Statistics - Computation, 01 natural sciences, Machine Learning (cs.LG), Hypothesis testing, Marginal likelihood, Numerical integration, 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics, Computation (stat.CO)

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/abs/2005.08334
https://hdl.handle.net/10016/39704
https://arxiv.org/abs/2005.08334
https://hdl.handle.net/20.500.11769/537718

Bayesian Integrals on Toric Varieties

Autori: Borinsky, Michael Sattelberger, Anna-Laura Sturmfels, Bernd a ďalší

Zdroj: SIAM JOURNAL ON APPLIED ALGEBRA AND GEOMETRY. 7(1):77-103

Predmety: toric varieties, positive geometries, marginal likelihood, Bayesian statistics, rejection sampling

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-329907

Stochastic Approximation with Biased MCMC for Expectation Maximization

Autori: Gruffaz, Samuel Kim, Kyurae Durmus, Alain, Oliviero a ďalší

Prispievatelia: Gruffaz, Samuel Kim, Kyurae Durmus, Alain, Oliviero a ďalší

Zdroj: AISTATS 2024 ; https://hal.science/hal-04735542 ; AISTATS 2024, May 2024, Valencia, Spain

Predmety: Mixed-effect models, Markov chain Monte Carlo, Expectation-maximization, Marginal likelihood, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]

Geografické téma: Valencia, Spain

Dostupnosť: https://hal.science/hal-04735542
https://hal.science/hal-04735542v1/document
https://hal.science/hal-04735542v1/file/gruffaz24a_final_publi.pdf