Bayesian Inference

The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been...

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Aineistotyyppi: Online
Kieli:englanti
Julkaistu: IntechOpen 2023
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Linkit:ONIX_20231201_9789535135784_610
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collection Directory of Open Access Books
description The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others. This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers.
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spelling doab-20.500.12854ir-1295012024-04-04T14:41:14Z Bayesian Inference Prieto Tejedor, Javier bayesian methods, gene expression, entrepreneurship, meta-analysis, investment, inverse problems thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others. This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers. 2023-12-01T15:32:35Z 2023-12-01T15:32:35Z 2017 book ONIX_20231201_9789535135784_610 9789535135784 9789535135777 9789535146155 https://directory.doabooks.org/handle/20.500.12854/129501 eng image/jpeg n/a https://www.intechopen.com/books/5964 https://mts.intechopen.com/storage/books/5964/authors_book/authors_book.pdf IntechOpen IntechOpen 10.5772/66264 10.5772/66264 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 9789535135784 9789535135777 9789535146155 IntechOpen 378 open access
spellingShingle bayesian methods, gene expression, entrepreneurship, meta-analysis, investment, inverse problems
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
Bayesian Inference
title Bayesian Inference
title_full Bayesian Inference
title_fullStr Bayesian Inference
title_full_unstemmed Bayesian Inference
title_short Bayesian Inference
title_sort bayesian inference
topic bayesian methods, gene expression, entrepreneurship, meta-analysis, investment, inverse problems
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
topic_facet bayesian methods, gene expression, entrepreneurship, meta-analysis, investment, inverse problems
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
url ONIX_20231201_9789535135784_610