Response modeling methodology: empirical modeling for engineering and science
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Singapore ; Hong Kong
World Scientific
2005
|
| Series: | Series on quality, reliability & engineering statistics
v. 8 |
| Subjects: | |
| Item Description: | Print version record |
| Physical Description: | 1 online resource (xxi, 435 pages) illustrations |
| ISBN: | 9789812569288 9812569286 1281880981 9781281880987 |
Staff View
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| 264 | 1 | |a Singapore ; Hong Kong |b World Scientific |c 2005 | |
| 300 | |a 1 online resource (xxi, 435 pages) |b illustrations | ||
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| 490 | 0 | |a Series on quality, reliability & engineering statistics |v v. 8 | |
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| 505 | 8 | |a This book introduces a new approach, denoted RMM, for an empirical modeling of a response variation, relating to both systematic variation and random variation. In the book, the developer of RMM discusses the required properties of empirical modeling and evaluates how current approaches conform to these requirements | |
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| 650 | 7 | |a Mathematical optimization |2 fast | |
| 650 | 7 | |a Reliability (Engineering) / Statistical methods |2 fast | |
| 650 | 4 | |a Reliability (Engineering) |x Statistical methods |a Engineering models |a Mathematical optimization | |
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Record in the Search Index
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| author | Shore, Haim |
| author_facet | Shore, Haim |
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| author_sort | Shore, Haim |
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| bvnumber | BV045341473 |
| collection | ZDB-4-ENC |
| contents | This book introduces a new approach, denoted RMM, for an empirical modeling of a response variation, relating to both systematic variation and random variation. In the book, the developer of RMM discusses the required properties of empirical modeling and evaluates how current approaches conform to these requirements |
| ctrlnum | (ZDB-4-ENC)ocm80244977 (OCoLC)80244977 (DE-599)BVBBV045341473 |
| dewey-full | 620/.00452 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 620 - Engineering and allied operations |
| dewey-raw | 620/.00452 |
| dewey-search | 620/.00452 |
| dewey-sort | 3620 3452 |
| dewey-tens | 620 - Engineering and allied operations |
| format | Electronic eBook |
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| id | DE-604.BV045341473 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:15:25Z |
| institution | BVB |
| isbn | 9789812569288 9812569286 1281880981 9781281880987 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030728177 |
| oclc_num | 80244977 |
| open_access_boolean | |
| physical | 1 online resource (xxi, 435 pages) illustrations |
| psigel | ZDB-4-ENC |
| publishDate | 2005 |
| publishDateSearch | 2005 |
| publishDateSort | 2005 |
| publisher | World Scientific |
| record_format | marc |
| series2 | Series on quality, reliability & engineering statistics |
| spelling | Shore, Haim Verfasser aut Response modeling methodology empirical modeling for engineering and science Haim Shore Singapore ; Hong Kong World Scientific 2005 1 online resource (xxi, 435 pages) illustrations txt rdacontent c rdamedia cr rdacarrier Series on quality, reliability & engineering statistics v. 8 Print version record This book introduces a new approach, denoted RMM, for an empirical modeling of a response variation, relating to both systematic variation and random variation. In the book, the developer of RMM discusses the required properties of empirical modeling and evaluates how current approaches conform to these requirements TECHNOLOGY & ENGINEERING / Engineering (General) bisacsh TECHNOLOGY & ENGINEERING / Reference bisacsh Engineering models fast Mathematical optimization fast Reliability (Engineering) / Statistical methods fast Reliability (Engineering) Statistical methods Engineering models Mathematical optimization Erscheint auch als Druck-Ausgabe Shore, Haim Response Modeling Methodology : Empirical Modeling For Engineering And Science Singapore : World Scientific, 2005 9789812561022 |
| spellingShingle | Shore, Haim Response modeling methodology empirical modeling for engineering and science This book introduces a new approach, denoted RMM, for an empirical modeling of a response variation, relating to both systematic variation and random variation. In the book, the developer of RMM discusses the required properties of empirical modeling and evaluates how current approaches conform to these requirements TECHNOLOGY & ENGINEERING / Engineering (General) bisacsh TECHNOLOGY & ENGINEERING / Reference bisacsh Engineering models fast Mathematical optimization fast Reliability (Engineering) / Statistical methods fast Reliability (Engineering) Statistical methods Engineering models Mathematical optimization |
| title | Response modeling methodology empirical modeling for engineering and science |
| title_auth | Response modeling methodology empirical modeling for engineering and science |
| title_exact_search | Response modeling methodology empirical modeling for engineering and science |
| title_full | Response modeling methodology empirical modeling for engineering and science Haim Shore |
| title_fullStr | Response modeling methodology empirical modeling for engineering and science Haim Shore |
| title_full_unstemmed | Response modeling methodology empirical modeling for engineering and science Haim Shore |
| title_short | Response modeling methodology |
| title_sort | response modeling methodology empirical modeling for engineering and science |
| title_sub | empirical modeling for engineering and science |
| topic | TECHNOLOGY & ENGINEERING / Engineering (General) bisacsh TECHNOLOGY & ENGINEERING / Reference bisacsh Engineering models fast Mathematical optimization fast Reliability (Engineering) / Statistical methods fast Reliability (Engineering) Statistical methods Engineering models Mathematical optimization |
| topic_facet | TECHNOLOGY & ENGINEERING / Engineering (General) TECHNOLOGY & ENGINEERING / Reference Engineering models Mathematical optimization Reliability (Engineering) / Statistical methods Reliability (Engineering) Statistical methods Engineering models Mathematical optimization |
| work_keys_str_mv | AT shorehaim responsemodelingmethodologyempiricalmodelingforengineeringandscience |