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...
Saved in:
Other Authors: | |
---|---|
Format: | Electronic Book Chapter |
Language: | English |
Published: |
IntechOpen
2017
|
Subjects: | |
Online Access: | DOAB: download the publication DOAB: description of the publication |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
MARC
LEADER | 00000naaaa2200000uu 4500 | ||
---|---|---|---|
001 | doab_20_500_12854_129501 | ||
005 | 20231201 | ||
003 | oapen | ||
006 | m o d | ||
007 | cr|mn|---annan | ||
008 | 20231201s2017 xx |||||o ||| 0|eng d | ||
020 | |a 66264 | ||
020 | |a 9789535135784 | ||
020 | |a 9789535135777 | ||
020 | |a 9789535146155 | ||
040 | |a oapen |c oapen | ||
024 | 7 | |a 10.5772/66264 |c doi | |
041 | 0 | |a eng | |
042 | |a dc | ||
072 | 7 | |a PBT |2 bicssc | |
100 | 1 | |a Prieto Tejedor, Javier |4 edt | |
700 | 1 | |a Prieto Tejedor, Javier |4 oth | |
245 | 1 | 0 | |a Bayesian Inference |
260 | |b IntechOpen |c 2017 | ||
300 | |a 1 electronic resource (378 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a 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. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/3.0/ |2 cc |4 https://creativecommons.org/licenses/by/3.0/ | ||
546 | |a English | ||
650 | 7 | |a Probability & statistics |2 bicssc | |
653 | |a bayesian methods, gene expression, entrepreneurship, meta-analysis, investment, inverse problems | ||
856 | 4 | 0 | |a www.oapen.org |u https://mts.intechopen.com/storage/books/5964/authors_book/authors_book.pdf |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/129501 |7 0 |z DOAB: description of the publication |