Large-scale inference: empirical Bayes methods for estimation, testing, and prediction
We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeate...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2010
|
| Schriftenreihe: | Institute of Mathematical Statistics monographs
1 |
| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 Volltext |
| Zusammenfassung: | We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xii, 263 pages) |
| ISBN: | 9780511761362 |
| DOI: | 10.1017/CBO9780511761362 |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV043940543 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 161206s2010 |||| o||u| ||||||eng d | ||
| 020 | |a 9780511761362 |c Online |9 978-0-511-76136-2 | ||
| 024 | 7 | |a 10.1017/CBO9780511761362 |2 doi | |
| 035 | |a (ZDB-20-CBO)CR9780511761362 | ||
| 035 | |a (OCoLC)839029437 | ||
| 035 | |a (DE-599)BVBBV043940543 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-12 |a DE-92 | ||
| 082 | 0 | |a 519.542 |2 22 | |
| 084 | |a QH 233 |0 (DE-625)141548: |2 rvk | ||
| 084 | |a SK 830 |0 (DE-625)143259: |2 rvk | ||
| 100 | 1 | |a Efron, Bradley |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Large-scale inference |b empirical Bayes methods for estimation, testing, and prediction |c Bradley Efron |
| 264 | 1 | |a Cambridge |b Cambridge University Press |c 2010 | |
| 300 | |a 1 online resource (xii, 263 pages) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Institute of Mathematical Statistics monographs |v 1 | |
| 500 | |a Title from publisher's bibliographic system (viewed on 05 Oct 2015) | ||
| 520 | |a We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples | ||
| 650 | 4 | |a Bayesian statistical decision theory | |
| 650 | 0 | 7 | |a Statistischer Test |0 (DE-588)4077852-6 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Bayes-Entscheidungstheorie |0 (DE-588)4144220-9 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Statistische Schlussweise |0 (DE-588)4182963-3 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Schätztheorie |0 (DE-588)4121608-8 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Statistische Schlussweise |0 (DE-588)4182963-3 |D s |
| 689 | 0 | 1 | |a Schätztheorie |0 (DE-588)4121608-8 |D s |
| 689 | 0 | 2 | |a Statistischer Test |0 (DE-588)4077852-6 |D s |
| 689 | 0 | 3 | |a Bayes-Entscheidungstheorie |0 (DE-588)4144220-9 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druckausgabe |z 978-0-521-19249-1 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druckausgabe |z 978-1-107-61967-8 |
| 856 | 4 | 0 | |u https://doi.org/10.1017/CBO9780511761362 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-20-CBO | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-029349513 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 966 | e | |u https://doi.org/10.1017/CBO9780511761362 |l BSB01 |p ZDB-20-CBO |q BSB_PDA_CBO |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1017/CBO9780511761362 |l FHN01 |p ZDB-20-CBO |q FHN_PDA_CBO |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804176881230020608 |
|---|---|
| any_adam_object | |
| author | Efron, Bradley |
| author_facet | Efron, Bradley |
| author_role | aut |
| author_sort | Efron, Bradley |
| author_variant | b e be |
| building | Verbundindex |
| bvnumber | BV043940543 |
| classification_rvk | QH 233 SK 830 |
| collection | ZDB-20-CBO |
| ctrlnum | (ZDB-20-CBO)CR9780511761362 (OCoLC)839029437 (DE-599)BVBBV043940543 |
| 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 |
| doi_str_mv | 10.1017/CBO9780511761362 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03398nmm a2200553zcb4500</leader><controlfield tag="001">BV043940543</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">161206s2010 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780511761362</subfield><subfield code="c">Online</subfield><subfield code="9">978-0-511-76136-2</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1017/CBO9780511761362</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-20-CBO)CR9780511761362</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)839029437</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV043940543</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-12</subfield><subfield code="a">DE-92</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519.542</subfield><subfield code="2">22</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">Efron, Bradley</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Large-scale inference</subfield><subfield code="b">empirical Bayes methods for estimation, testing, and prediction</subfield><subfield code="c">Bradley Efron</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cambridge</subfield><subfield code="b">Cambridge University Press</subfield><subfield code="c">2010</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (xii, 263 pages)</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">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Institute of Mathematical Statistics monographs</subfield><subfield code="v">1</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Title from publisher's bibliographic system (viewed on 05 Oct 2015)</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bayesian statistical decision theory</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Statistischer Test</subfield><subfield code="0">(DE-588)4077852-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</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="650" ind1="0" ind2="7"><subfield code="a">Statistische Schlussweise</subfield><subfield code="0">(DE-588)4182963-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Schätztheorie</subfield><subfield code="0">(DE-588)4121608-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Statistische Schlussweise</subfield><subfield code="0">(DE-588)4182963-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Schätztheorie</subfield><subfield code="0">(DE-588)4121608-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Statistischer Test</subfield><subfield code="0">(DE-588)4077852-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><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="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druckausgabe</subfield><subfield code="z">978-0-521-19249-1</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druckausgabe</subfield><subfield code="z">978-1-107-61967-8</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1017/CBO9780511761362</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-20-CBO</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-029349513</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/CBO9780511761362</subfield><subfield code="l">BSB01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">BSB_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1017/CBO9780511761362</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-20-CBO</subfield><subfield code="q">FHN_PDA_CBO</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV043940543 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:13Z |
| institution | BVB |
| isbn | 9780511761362 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029349513 |
| oclc_num | 839029437 |
| open_access_boolean | |
| owner | DE-12 DE-92 |
| owner_facet | DE-12 DE-92 |
| physical | 1 online resource (xii, 263 pages) |
| psigel | ZDB-20-CBO ZDB-20-CBO BSB_PDA_CBO ZDB-20-CBO FHN_PDA_CBO |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | Cambridge University Press |
| record_format | marc |
| series2 | Institute of Mathematical Statistics monographs |
| spelling | Efron, Bradley Verfasser aut Large-scale inference empirical Bayes methods for estimation, testing, and prediction Bradley Efron Cambridge Cambridge University Press 2010 1 online resource (xii, 263 pages) txt rdacontent c rdamedia cr rdacarrier Institute of Mathematical Statistics monographs 1 Title from publisher's bibliographic system (viewed on 05 Oct 2015) We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples Bayesian statistical decision theory Statistischer Test (DE-588)4077852-6 gnd rswk-swf Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd rswk-swf Statistische Schlussweise (DE-588)4182963-3 gnd rswk-swf Schätztheorie (DE-588)4121608-8 gnd rswk-swf Statistische Schlussweise (DE-588)4182963-3 s Schätztheorie (DE-588)4121608-8 s Statistischer Test (DE-588)4077852-6 s Bayes-Entscheidungstheorie (DE-588)4144220-9 s 1\p DE-604 Erscheint auch als Druckausgabe 978-0-521-19249-1 Erscheint auch als Druckausgabe 978-1-107-61967-8 https://doi.org/10.1017/CBO9780511761362 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Efron, Bradley Large-scale inference empirical Bayes methods for estimation, testing, and prediction Bayesian statistical decision theory Statistischer Test (DE-588)4077852-6 gnd Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Statistische Schlussweise (DE-588)4182963-3 gnd Schätztheorie (DE-588)4121608-8 gnd |
| subject_GND | (DE-588)4077852-6 (DE-588)4144220-9 (DE-588)4182963-3 (DE-588)4121608-8 |
| title | Large-scale inference empirical Bayes methods for estimation, testing, and prediction |
| title_auth | Large-scale inference empirical Bayes methods for estimation, testing, and prediction |
| title_exact_search | Large-scale inference empirical Bayes methods for estimation, testing, and prediction |
| title_full | Large-scale inference empirical Bayes methods for estimation, testing, and prediction Bradley Efron |
| title_fullStr | Large-scale inference empirical Bayes methods for estimation, testing, and prediction Bradley Efron |
| title_full_unstemmed | Large-scale inference empirical Bayes methods for estimation, testing, and prediction Bradley Efron |
| title_short | Large-scale inference |
| title_sort | large scale inference empirical bayes methods for estimation testing and prediction |
| title_sub | empirical Bayes methods for estimation, testing, and prediction |
| topic | Bayesian statistical decision theory Statistischer Test (DE-588)4077852-6 gnd Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Statistische Schlussweise (DE-588)4182963-3 gnd Schätztheorie (DE-588)4121608-8 gnd |
| topic_facet | Bayesian statistical decision theory Statistischer Test Bayes-Entscheidungstheorie Statistische Schlussweise Schätztheorie |
| url | https://doi.org/10.1017/CBO9780511761362 |
| work_keys_str_mv | AT efronbradley largescaleinferenceempiricalbayesmethodsforestimationtestingandprediction |