Bayesian decision analysis: principles and practice
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge [u.a.]
Cambridge Univ. Press
2010
|
| Edition: | 1. publ. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis Klappentext |
| Item Description: | Includes bibliographical references and index |
| Physical Description: | IX, 338 S. graph. Darst. |
| ISBN: | 9780521764544 0521764548 |
Staff View
MARC
| LEADER | 00000nam a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV040340237 | ||
| 003 | DE-604 | ||
| 005 | 20120918 | ||
| 007 | t | ||
| 008 | 120730s2010 d||| |||| 00||| eng d | ||
| 020 | |a 9780521764544 |9 978-0-521-76454-4 | ||
| 020 | |a 0521764548 |9 0-521-76454-8 | ||
| 035 | |a (OCoLC)731384228 | ||
| 035 | |a (DE-599)BVBBV040340237 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-739 |a DE-824 | ||
| 082 | 0 | |a 519.542 | |
| 084 | |a QH 233 |0 (DE-625)141548: |2 rvk | ||
| 084 | |a SK 830 |0 (DE-625)143259: |2 rvk | ||
| 100 | 1 | |a Smith, Jim Q. |d 1953- |e Verfasser |0 (DE-588)1013119983 |4 aut | |
| 245 | 1 | 0 | |a Bayesian decision analysis |b principles and practice |c Jim Q. Smith |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Cambridge [u.a.] |b Cambridge Univ. Press |c 2010 | |
| 300 | |a IX, 338 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
| 650 | 4 | |a Bayesian statistical decision theory | |
| 650 | 4 | |a Mathematical statistics | |
| 650 | 0 | 7 | |a Bayes-Entscheidungstheorie |0 (DE-588)4144220-9 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Bayes-Entscheidungstheorie |0 (DE-588)4144220-9 |D s |
| 689 | 0 | |5 DE-604 | |
| 856 | 4 | 2 | |m Digitalisierung UB Passau |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025194536&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 856 | 4 | 2 | |m Digitalisierung UB Passau |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025194536&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |3 Klappentext |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-025194536 | ||
Record in the Search Index
| _version_ | 1804149373226975232 |
|---|---|
| adam_text | Contents
Preface page
viii
Part I Foundations of Decision Modelling
1
Introduction
3
1.1
Getting started
9
1.2
A simple framework for decision making
9
1.3
Bayes
rale in court
20
1.4
Models with contingent decisions
24
1.5
Summary
26
1.6
Exercises
26
2
Explanations of processes and trees
28
2.1
Introduction
28
2.2
Using trees to explain how situations might develop
29
2.3
Decision trees
34
2.4
Some practical issues*
41
2.5
Rollback decision trees
46
2.6
Normal form trees
54
2.7
Temporal coherence and episodic trees*
58
2.8
Summary
59
2.9
Exercises
60
3
Utilities and rewards
62
3.1
Introduction
62
3.2
Utility and the value of a consequence
64
3.3
Properties and illustrations of rational choice
77
3.4
Eliciting a utility function with a dimensional attribute
82
3.5
The expected value of perfect information
84
3.6
Bayes
decisions when reward distributions are continuous
86
3.7
Calculating expected losses
87
3.8
Bayes
decisions under conflict*
91
3.9
Summary
98
3.10
Exercises
99
4
Subjective
probability and its elicitation
103
4.1
Defining subjective probabilities
103
4.2
On formal definitions of subjective probabilities
108
4.3
Improving the assessment of prior information
112
4.4
Calibration and successful probability predictions
118
4.5
Scoring forecasters
123
4.6
Summary
127
4.7
Exercises
128
5
Bayesian inference for decision analysis
131
5.1
Introduction
131
5.2
The basics of Bayesian inference
133
5.3
Prior to posterior analyses
136
5.4
Distributions which are closed under sampling
139
5.5
Posterior densities for absolutely continuous parameters
140
5.6
Some standard inferences using conjugate families
145
5.7
Non-conjugate inference*
151
5.8
Discrete mixtures and model selection
154
5.9
How a decision analysis can use Bayesian inferences
158
5.10
Summary
162
5.11
Exercises
162
Part II Multidimensional Decision Modelling
6
Multiattribute utility theory
169
6.1
Introduction
169
6.2
Utility independence
171
6.3
Some general characterisation results
177
6.4
Eliciting a utility function
178
6.5
Value independent attributes
180
6.6
Decision conferencing and utility elicitation
187
6.7
Real-time support within decision processes
193
6.8
Summary
196
6.9
Exercises
196
7
Bayesian networks
199
7.1
Introduction
199
7.2
Relevance, informativeness and independence
200
7.3
Bayesian networks and DAGs
204
7.4
Eliciting a Bayesian network: a protocol
217
7.5
Efficient storage on Bayesian networks
224
7.6
Junction trees and probability propagation
229
7.7
Bayesian networks and other graphs
239
7.8
Summary
243
7.9
Exercises
243
8
Graphs, decisions and causality
248
8.1
Influence diagrams
248
8.2
Controlled causation
261
8.3
D
AGs and causality
265
8.4
Time series models*
276
8.5
Summary
279
8.6
Exercises
280
9
Multidimensional learning
282
9.1
Introduction
282
9.2
Separation, orthogonality and independence
286
9.3
Estimating probabilities on trees
292
9.4
Estimating probabilities in Bayesian networks
298
9.5
Technical issues about structured learning*
302
9.6
Robustness of inference given copious data*
306
9.7
Summary
313
9.8
Exercises
313
10
Conclusions
318
10.1
A summary of what has been demonstrated above
318
10.2
Other types of decision analyses
319
References
322
Index
335
Bayesian
decision analysis supports principled decision making
in complex but structured domains. The focus of this textbook
is on the faithful representation and conjugate analyses of
discrete decision problems. It takes the reader from a formal
analysis of simple decision problems to a careful analysis of the
sometimes very complex and data-rich structures confronted
by practitioners. The book contains basic material on subjective
probability theory and multi-attribute utility theory, event and
decision trees, Bayesian networks, influence diagrams and causal
Bayesian networks. The author demonstrates when and how the
theory can be applied successfully to a given decision problem;
how data can be sampled and expert judgements elicited to
support this analysis; and when and how an effective Bayesian
decision analysis can be implemented.
f
Evolving from a third-year undergraduate course taught by the
author over many years, all of the material in this book will be
accessible to a student who has completed introductory courses
in probability and mathematical statistics.
|
| any_adam_object | 1 |
| author | Smith, Jim Q. 1953- |
| author_GND | (DE-588)1013119983 |
| author_facet | Smith, Jim Q. 1953- |
| author_role | aut |
| author_sort | Smith, Jim Q. 1953- |
| author_variant | j q s jq jqs |
| building | Verbundindex |
| bvnumber | BV040340237 |
| classification_rvk | QH 233 SK 830 |
| ctrlnum | (OCoLC)731384228 (DE-599)BVBBV040340237 |
| dewey-full | 519.542 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.542 |
| dewey-search | 519.542 |
| dewey-sort | 3519.542 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | 1. publ. |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01772nam a2200409zc 4500</leader><controlfield tag="001">BV040340237</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20120918 </controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">120730s2010 d||| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780521764544</subfield><subfield code="9">978-0-521-76454-4</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">0521764548</subfield><subfield code="9">0-521-76454-8</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)731384228</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV040340237</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-739</subfield><subfield code="a">DE-824</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519.542</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">QH 233</subfield><subfield code="0">(DE-625)141548:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">SK 830</subfield><subfield code="0">(DE-625)143259:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Smith, Jim Q.</subfield><subfield code="d">1953-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1013119983</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Bayesian decision analysis</subfield><subfield code="b">principles and practice</subfield><subfield code="c">Jim Q. Smith</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1. publ.</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge [u.a.]</subfield><subfield code="b">Cambridge Univ. Press</subfield><subfield code="c">2010</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">IX, 338 S.</subfield><subfield code="b">graph. Darst.</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bayesian statistical decision theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical statistics</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Bayes-Entscheidungstheorie</subfield><subfield code="0">(DE-588)4144220-9</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Bayes-Entscheidungstheorie</subfield><subfield code="0">(DE-588)4144220-9</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Digitalisierung UB Passau</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025194536&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Digitalisierung UB Passau</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025194536&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Klappentext</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-025194536</subfield></datafield></record></collection> |
| id | DE-604.BV040340237 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T00:22:00Z |
| institution | BVB |
| isbn | 9780521764544 0521764548 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025194536 |
| oclc_num | 731384228 |
| open_access_boolean | |
| owner | DE-739 DE-824 |
| owner_facet | DE-739 DE-824 |
| physical | IX, 338 S. graph. Darst. |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | Cambridge Univ. Press |
| record_format | marc |
| spelling | Smith, Jim Q. 1953- Verfasser (DE-588)1013119983 aut Bayesian decision analysis principles and practice Jim Q. Smith 1. publ. Cambridge [u.a.] Cambridge Univ. Press 2010 IX, 338 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Bayesian statistical decision theory Mathematical statistics Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd rswk-swf Bayes-Entscheidungstheorie (DE-588)4144220-9 s DE-604 Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025194536&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025194536&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Smith, Jim Q. 1953- Bayesian decision analysis principles and practice Bayesian statistical decision theory Mathematical statistics Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd |
| subject_GND | (DE-588)4144220-9 |
| title | Bayesian decision analysis principles and practice |
| title_auth | Bayesian decision analysis principles and practice |
| title_exact_search | Bayesian decision analysis principles and practice |
| title_full | Bayesian decision analysis principles and practice Jim Q. Smith |
| title_fullStr | Bayesian decision analysis principles and practice Jim Q. Smith |
| title_full_unstemmed | Bayesian decision analysis principles and practice Jim Q. Smith |
| title_short | Bayesian decision analysis |
| title_sort | bayesian decision analysis principles and practice |
| title_sub | principles and practice |
| topic | Bayesian statistical decision theory Mathematical statistics Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd |
| topic_facet | Bayesian statistical decision theory Mathematical statistics Bayes-Entscheidungstheorie |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025194536&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025194536&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT smithjimq bayesiandecisionanalysisprinciplesandpractice |