Výsledky vyhľadávania - "Stochastic EM algorithm"

The Moore and Bilikam model and Burr XII sub-model under progressively type-II censoring scheme

Autori: Mehdi BAZYAR Einolah DEİRİ Ezzatallah BALOUİ JAMKHANEH

Zdroj: Volume: 52, Issue: 3 768-784
Hacettepe Journal of Mathematics and Statistics

Predmety: E-Bayesian estimation, stochastic EM algorithm, Burr XII, Moore andBilikam family, progressively type-II censoring, failure data, İstatistik, Statistics, 0101 mathematics, 01 natural sciences

Popis súboru: application/pdf

Prístupová URL adresa: https://dergipark.org.tr/tr/pub/hujms/issue/77353/1082101

Estimation, Prediction and Life Testing Plan for the Exponentiated Gumbel Type-II Progressive Censored Data

Autori: Kousik Maiti Suchandan Kayal

Zdroj: Revstat Statistical Journal, Vol 21, Iss 4 (2023)

Predmety: MH algorithm, importance sampling, Statistics, stochastic EM algorithm, optimal censoring, EM algorithm, Lindley's approximation, Probabilities. Mathematical statistics, QA273-280, HA1-4737

Prístupová URL adresa: https://doaj.org/article/20a8024127cb43e9b654aebcfcef3a6a

Selecting the model for multiple imputation of missing data: Just use an IC!

Autori: Noghrehchi, F Stoklosa, J Penev, S a ďalší

Zdroj: Stat Med

Predmety: 4202 Epidemiology, anzsrc-for: 4202 Epidemiology, 01 natural sciences, anzsrc-for: 0104 Statistics, Bias, 2.5 Research design and methodologies (aetiology), Humans, Computer Simulation, 0101 mathematics, information criteria, Research Articles, Likelihood Functions, anzsrc-for: 42 Health Sciences, imputation model selection, stochastic EM algorithm, 42 Health Sciences, Bayes Theorem, missing data analysis, anzsrc-for: 4905 Statistics, 8.4 Research design and methodologies (health services), 4905 Statistics, anzsrc-for: 49 Mathematical Sciences, 49 Mathematical Sciences, Generic health relevance, Algorithms, anzsrc-for: 1117 Public Health and Health Services

Popis súboru: application/pdf

Prístupová URL adresa: https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/sim.8915
https://pubmed.ncbi.nlm.nih.gov/33629367
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8248419
https://pubmed.ncbi.nlm.nih.gov/33629367/
https://www.ncbi.nlm.nih.gov/pubmed/33629367
https://onlinelibrary.wiley.com/doi/full/10.1002/sim.8915

Estimation of a Simple Structure in a Multidimensional IRT Model Using Structure Regularization

Autori: Ryosuke Shimmura Joe Suzuki

Zdroj: Entropy, Vol 26, Iss 1, p 44 (2023)

Predmety: prenet penalty, lasso, simple structure, stochastic EM algorithm, Science, Astrophysics, QB460-466, Physics, QC1-999

Relation: https://www.mdpi.com/1099-4300/26/1/44; https://doaj.org/toc/1099-4300; https://doaj.org/article/92df911c56cb487da8514668903018cb

Dostupnosť: https://doi.org/10.3390/e26010044
https://doaj.org/article/92df911c56cb487da8514668903018cb

Model-based clustering for flow and mass cytometry data with clinical information

Autori: Ko Abe Kodai Minoura Yuka Maeda a ďalší

Zdroj: BMC Bioinformatics, Vol 21, Iss S13, Pp 1-15 (2020)

Predmety: Flow cytomety, Mass cytometory, Bayesian mixture model, Stochastic EM algorithm, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5

Popis súboru: electronic resource

Relation: http://link.springer.com/article/10.1186/s12859-020-03671-7; https://doaj.org/toc/1471-2105

Prístupová URL adresa: https://doaj.org/article/efa544860400467b83c195a8f91a2d9a

Statistical Inference for Competing Risks Model with Adaptive Progressively Type-II Censored Gompertz Life Data Using Industrial and Medical Applications

Autori: Muqrin A. Almuqrin Mukhtar M. Salah Essam A. Ahmed

Zdroj: Mathematics ; Volume 10 ; Issue 22 ; Pages: 4274

Predmety: Gompertz distribution, competing risks model, adaptive progressively Type-II censoring, maximum likelihood estimation, stochastic EM algorithm, bootstrap methods, delta method, Bayes estimator, Markov chain Monte Carlo

Popis súboru: application/pdf

Relation: D1: Probability and Statistics; https://dx.doi.org/10.3390/math10224274

Dostupnosť: https://doi.org/10.3390/math10224274

An improved stochasticEMalgorithm for large‐scale full‐information item factor analysis

Autori: Zhang, Siliang Chen, Yunxiao Liu, Yang

Zdroj: British Journal of Mathematical and Statistical Psychology. 73:44-71

Predmety: Stochastic Processes, 05 social sciences, stochastic EM algorithm, multidimensional item response theory, 01 natural sciences, rejection sampling, 0504 sociology, Gibbs sampler, full-information item factor analysis, Humans, Regression Analysis, Computer Simulation, 0101 mathematics, Factor Analysis, Statistical, Algorithms, proximal gradient descent

Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/30511445
https://www.onlinelibrary.wiley.com/doi/abs/10.1111/bmsp.12153
https://bpspsychub.onlinelibrary.wiley.com/doi/abs/10.1111/bmsp.12153
https://europepmc.org/article/MED/30511445
https://www.ncbi.nlm.nih.gov/pubmed/30511445
http://eprints.lse.ac.uk/91027/
https://pubmed.ncbi.nlm.nih.gov/30511445/
http://eprints.lse.ac.uk/91027/

Stochastic proximal-gradient algorithms for penalized mixed models

Autori: Gersende Fort Edouard Ollier Adeline Samson a ďalší

Prispievatelia: Gersende Fort Edouard Ollier Adeline Samson a ďalší

Zdroj: Statistics and Computing. 29:231-253

Predmety: Methodology (stat.ME), FOS: Computer and information sciences, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Stochastic Approximation, Non-linear mixed effect models, Stochastic EM algorithm, Proximal-Gradient algorithm, Stochastic Gradient, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], Statistics - Computation, Statistics - Methodology, Computation (stat.CO)

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/pdf/1704.08891
http://arxiv.org/abs/1704.08891
https://hal.archives-ouvertes.fr/hal-01526281
https://link.springer.com/article/10.1007/s11222-018-9805-7
https://dblp.uni-trier.de/db/journals/sac/sac29.html#FortOS19
https://doi.org/10.1007/s11222-018-9805-7
https://hal.archives-ouvertes.fr/hal-01526281/document
https://hal.science/hal-01526281v1/document
https://hal.science/hal-01526281v1
https://doi.org/10.1007/s11222-018-9805-7

Parameter estimation of complex mixed models based on meta-model approach

Autori: Barbillon, Pierre Barthelemy, Célia Leclercq-Samson, Adeline a ďalší

Prispievatelia: Barbillon, Pierre Barthelemy, Célia Leclercq-Samson, Adeline a ďalší

Zdroj: Statistics and Computing. 27:1111-1128

Predmety: [SDV] Life Sciences [q-bio], MCMC methods, Gaussian Process emulator, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], FOS: Mathematics, Mathematics - Statistics Theory, Stochastic EM algorithm, Statistics Theory (math.ST), Mixed models, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]

Popis súboru: application/pdf

Prístupová URL adresa: https://hal.archives-ouvertes.fr/hal-01162351/file/versionpreprint.pdf
http://arxiv.org/abs/1506.03313
https://hal.science/hal-01162351v1/document
https://hal.science/hal-01162351v1
https://doi.org/10.1007/s11222-016-9674-x
https://hal.science/hal-01600700v1
https://hal-agroparistech.archives-ouvertes.fr/hal-01162351v1
https://link.springer.com/article/10.1007/s11222-016-9674-x/fulltext.html
https://link.springer.com/article/10.1007/s11222-016-9674-x
https://link.springer.com/article/10.1007/s11222-016-9674-x?view=classic
https://doi.org/10.1007/s11222-016-9674-x
https://hal.archives-ouvertes.fr/hal-01162351/file/versionpreprint.pdf

Exact Sampling from Conditional Boolean Models with Applications to Maximum Likelihood Inference

Autori: Van Lieshout, M. N. M. Van Zwet, E. W.

Zdroj: Advances in Applied Probability, 2001 Jun 01. 33(2), 339-353.

Prístupová URL adresa: https://www.jstor.org/stable/1428256

Generation of "Similar" Images from a Given Discrete Image

Autori: Kozintsev, Boris Kedem, Benjamin

Zdroj: Journal of Computational and Graphical Statistics, 2000 Jun 01. 9(2), 286-302.

Prístupová URL adresa: https://www.jstor.org/stable/1390655

Deep Gaussian mixture models

Autori: Viroli, Cinzia McLachlan, Geoffrey J.

Zdroj: Statistics and Computing. 29:43-51

Predmety: FOS: Computer and information sciences, Computer Science - Machine Learning, Unsupervised classification, Mixtures of factor analyzers, Stochastic EM algorithm, Theoretical Computer Science, Statistics and Probability, Statistics, Probability and Uncertainty, Computational Theory and Mathematics, Machine Learning (stat.ML), 02 engineering and technology, 01 natural sciences, Machine Learning (cs.LG), 1804 Statistics, Statistics - Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, Probability and Uncertainty, 2613 Statistics and Probability, 0101 mathematics, 2614 Theoretical Computer Science, 1703 Computational Theory and Mathematics

Prístupová URL adresa: https://espace.library.uq.edu.au/view/UQ:729089/UQ729089_OA.pdf
http://arxiv.org/abs/1711.06929
https://espace.library.uq.edu.au/view/UQ:729089
https://link.springer.com/10.1007/s11222-017-9793-z
https://espace.library.uq.edu.au/view/UQ:729089/UQ729089_OA.pdf
https://core.ac.uk/display/157825628
https://cris.unibo.it/handle/11585/665534
https://dblp.uni-trier.de/db/journals/corr/corr1711.html#abs-1711-06929
https://hdl.handle.net/11585/665534
http://www.kluweronline.com/issn/0960-3174
https://doi.org/10.1007/s11222-017-9793-z

ExpectationMaximization.jl: A simple but generic implementation of Expectation Maximization algorithms to fit mixture models

Autori: Métivier, David Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA) Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier a ďalší

Prispievatelia: Métivier, David Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA) Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier a ďalší

Zdroj: https://hal.inrae.fr/hal-04784091 ; 2024, ⟨swh:1:dir:8ed1911c8e0fc5d86663141fe4f7b42698021ad6;origin=https://hal.archives-ouvertes.fr/hal-04784091.

Predmety: Expectation Maximization, Julia programming language, Stochastic em algorithm, Mixture models, Clustering, Generic codes, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]

Dostupnosť: https://hal.inrae.fr/hal-04784091
https://hal.inrae.fr/hal-04784091v1/document
https://hal.inrae.fr/hal-04784091v1/file/ExpectationMaximization.jl-v0.2.3.zip

Convergent stochastic Expectation Maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimation

Autori: Allassonnière, Stéphanie Kuhn, Estelle ProdInra, Archive Ouverte a ďalší

Prispievatelia: Allassonnière, Stéphanie Kuhn, Estelle ProdInra, Archive Ouverte a ďalší

Zdroj: Computational Statistics & Data Analysis. 91:4-19

Predmety: deformable template, high dimension, [SDV]Life Sciences [q-bio], stochastic em algorithm, maximum likelihood estimation, Mathematics - Statistics Theory, Statistics Theory (math.ST), 02 engineering and technology, 01 natural sciences, 6. Clean water, mcmc, [SDV] Life Sciences [q-bio], missing variable, geometric variability, anisotropic mala, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics

Prístupová URL adresa: http://arxiv.org/pdf/1207.5938
http://arxiv.org/abs/1207.5938
http://www.sciencedirect.com/science/article/pii/S0167947315001164
https://ideas.repec.org/a/eee/csdana/v91y2015icp4-19.html
https://ui.adsabs.harvard.edu/abs/2012arXiv1207.5938A/abstract
https://econpapers.repec.org/RePEc:eee:csdana:v:91:y:2015:i:c:p:4-19
https://pubag.nal.usda.gov/catalog/6035591
https://www.sciencedirect.com/science/article/pii/S0167947315001164
https://hal.science/hal-01535284v1
https://doi.org/10.1016/j.csda.2015.04.011

A non linear mixed effects model of plant growth and estimation via stochastic variants of the EM algorithm

Autori: Baey, Charlotte Trevezas, Samis Cournède, Paul-Henry

Prispievatelia: Baey, Charlotte Trevezas, Samis Cournède, Paul-Henry

Zdroj: Communications in Statistics - Theory and Methods. 45:1643-1669

Predmety: MCMC methods, plant growth model, [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.TH] Statistics [stat]/Statistics Theory [stat.TH], nonlinear mixed effects model, stochastic EM algorithm, 0101 mathematics, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], 01 natural sciences, sugar-beet plant

Popis súboru: application/pdf

Prístupová URL adresa: https://hal.archives-ouvertes.fr/hal-01068327/file/baey_et_al_revised2.pdf
https://ideas.repec.org/a/taf/lstaxx/v45y2016i6p1643-1669.html
https://hal.archives-ouvertes.fr/hal-01068327v1
https://www.tandfonline.com/doi/full/10.1080/03610926.2014.930909
https://hal.archives-ouvertes.fr/hal-01068327/document

Dynamic frailty models based on compound birth–death processes

Autori: Putter, H. Houwelingen, H.C. van

Zdroj: Biostatistics. 16:550-564

Predmety: Time-varying frailties, Likelihood Functions, Stochastic Processes, Models, Statistical, Compound birth-death processes, Dynamic frailty processes, Stochastic EM algorithm, Neoplasms, Experimental, Biostatistics, Survival Analysis, 01 natural sciences, Rats, Unobserved heterogeneity, Recurrence, 13. Climate action, Animals, Humans, Computer Simulation, Female, 0101 mathematics, Monte Carlo Method, Algorithms, Proportional Hazards Models

Prístupová URL adresa: https://academic.oup.com/biostatistics/article-pdf/16/3/550/17741825/kxv002.pdf
https://pubmed.ncbi.nlm.nih.gov/25681608
https://www.ncbi.nlm.nih.gov/pubmed/25681608
https://academic.oup.com/biostatistics/article/16/3/550/269862
https://www.narcis.nl/publication/RecordID/oai%3Ascholarlypublications.universiteitleiden.nl%3Aitem_2994289
https://pubmed.ncbi.nlm.nih.gov/25681608/
http://biostatistics.oxfordjournals.org/content/16/3/550
https://academic.oup.com/biostatistics/article-abstract/16/3/550/269862/Dynamic-frailty-models-based-on-compound-birth
https://hdl.handle.net/1887/97217

Estimation and filtering by reversible jump MCMC for a doubly stochastic Poisson model for ultra-high-frequency financial data

Autori: CENTANNI, Silvia MINOZZO, Marco

Zdroj: Statistical Modelling. 6:97-118

Predmety: Intraday data, Marked point process, News arrival, Option pricing, Reversible jump Markov chain Monte Carlo, Stochastic EM algorithm, Marked point processes, 0101 mathematics, 01 natural sciences

Prístupová URL adresa: http://smj.sagepub.com/lookup/doi/10.1191/1471082X06st112oa
https://journals.sagepub.com/doi/abs/10.1191/1471082X06st112oa
https://hdl.handle.net/11562/313886
https://hdl.handle.net/11562/231916

A Stochastic EM Algorithm for Progressively Censored Data Analysis

Autori: Mimi Zhang Zhi-Sheng Ye Min Xie

Zdroj: Quality and Reliability Engineering International. 30:711-722

Predmety: Progressively censored data, Lifetime distribution, Stochastic EM algorithm, 0101 mathematics, 01 natural sciences

Popis súboru: application/pdf

Prístupová URL adresa: http://www.tara.tcd.ie/bitstream/2262/90020/3/A%20Stochastic%20EM%20Algorithm%20for%20Progressively%20Censored%20Data%20Analysis.pdf
http://www.tara.tcd.ie/bitstream/2262/90020/3/A%20Stochastic%20EM%20Algorithm%20for%20Progressively%20Censored%20Data%20Analysis.pdf
http://www.tara.tcd.ie/handle/2262/90020
https://dblp.uni-trier.de/db/journals/qre/qre30.html#ZhangY014
https://onlinelibrary.wiley.com/doi/10.1002/qre.1522
https://hdl.handle.net/2262/90020
http://people.tcd.ie/zhangm3

Stochastic EM algorithm for doubly interval-censored data

Autori: Dejardin, David LESAFFRE, Emmanuel

Zdroj: Biostatistics. 14:766-778

Predmety: Stochastic Processes, Cox proportional hazard, Doubly interval censored, stochastic EM algorithm, EMC NIHES-01-66-01, Breast Neoplasms, Survival Analysis, 01 natural sciences, Treatment Outcome, Antineoplastic Combined Chemotherapy Protocols, Humans, Computer Simulation, Female, 0101 mathematics, Algorithms, Proportional Hazards Models, Randomized Controlled Trials as Topic

Popis súboru: application/pdf

Prístupová URL adresa: https://academic.oup.com/biostatistics/article-pdf/14/4/766/1055036/kxt019.pdf
https://pubmed.ncbi.nlm.nih.gov/23728851
https://pure.eur.nl/en/publications/5b62afe7-809a-429d-8ed0-2a872ae17360
https://doi.org/10.1093/biostatistics/kxt019
https://www.ncbi.nlm.nih.gov/pubmed/23728851
https://pubmed.ncbi.nlm.nih.gov/23728851/
https://repub.eur.nl/pub/66366/
https://academic.oup.com/biostatistics/article/14/4/766/370598
http://core.ac.uk/display/34623315
https://paperity.org/p/38737479/stochastic-em-algorithm-for-doubly-interval-censored-data
http://hdl.handle.net/1942/16128

Comparison of EM and SEM Algorithms in Poisson Regression Models: A Simulation Study

Autori: Faria, Susana Soromenho, Gilda Universidade do Minho

Prispievatelia: Faria, Susana Soromenho, Gilda Universidade do Minho

Zdroj: Communications in Statistics - Simulation and Computation. 41:497-509

Predmety: Mixture poisson regression models, Simulation study, Stochastic EM algorithm, Stochastic EM alg, 0101 mathematics, EM algorithm, Maximum likelihood estimation, 01 natural sciences

Popis súboru: application/pdf

Prístupová URL adresa: https://hal.archives-ouvertes.fr/hal-00767496/file/PEER_stage2_10.1080%252F03610918.2011.594534.pdf
https://www.tandfonline.com/doi/abs/10.1080/03610918.2011.594534
https://doi.org/10.1080/03610918.2011.594534
https://dblp.uni-trier.de/db/journals/cssc/cssc41.html#FariaS12
https://repositorium.sdum.uminho.pt/handle/1822/20865
https://hdl.handle.net/1822/20865