Non-Uniform Random Variate Generation:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer New York
1986
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Thls text ls about one small fteld on the crossroads of statlstlcs, operatlons research and computer sclence. Statistleians need random number generators to test and compare estlmators before uslng them ln real l!fe. In operatlons research, random numbers are a key component ln !arge scale slmulatlons. Computer sclen tlsts need randomness ln program testlng, game playlng and comparlsons of algo rlthms. The appl!catlons are wlde and varled. Yet all depend upon the same com puter generated random numbers. Usually, the randomness demanded by an appl!catlon has some bullt-ln structure: typlcally, one needs more than just a sequence of Independent random blts or Independent uniform [0,1] random vari ables. Some users need random variables wlth unusual densltles, or random com blnatorlal objects wlth speclftc propertles, or random geometrlc objects, or ran dom processes wlth weil deftned dependence structures. Thls ls preclsely the sub ject area of the book, the study of non-uniform random varlates. The plot evolves around the expected complexlty of random varlate genera tlon algorlthms. We set up an ldeal!zed computatlonal model (wlthout overdolng lt), we lntroduce the notlon of unlformly bounded expected complexlty, and we study upper and lower bounds for computatlonal complexlty. In short, a touch of computer sclence ls added to the fteld. To keep everythlng abstract, no tlmlngs or computer programs are lncluded. Thls was a Iabor of Iove. George Marsagl!a created CS690, a course on ran dom number generat!on at the School of Computer Sclence of McG!ll Unlverslty |
| Beschreibung: | 1 Online-Ressource (XVI, 843 p) |
| ISBN: | 9781461386438 9781461386452 |
| DOI: | 10.1007/978-1-4613-8643-8 |
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| 500 | |a Thls text ls about one small fteld on the crossroads of statlstlcs, operatlons research and computer sclence. Statistleians need random number generators to test and compare estlmators before uslng them ln real l!fe. In operatlons research, random numbers are a key component ln !arge scale slmulatlons. Computer sclen tlsts need randomness ln program testlng, game playlng and comparlsons of algo rlthms. The appl!catlons are wlde and varled. Yet all depend upon the same com puter generated random numbers. Usually, the randomness demanded by an appl!catlon has some bullt-ln structure: typlcally, one needs more than just a sequence of Independent random blts or Independent uniform [0,1] random vari ables. Some users need random variables wlth unusual densltles, or random com blnatorlal objects wlth speclftc propertles, or random geometrlc objects, or ran dom processes wlth weil deftned dependence structures. Thls ls preclsely the sub ject area of the book, the study of non-uniform random varlates. The plot evolves around the expected complexlty of random varlate genera tlon algorlthms. We set up an ldeal!zed computatlonal model (wlthout overdolng lt), we lntroduce the notlon of unlformly bounded expected complexlty, and we study upper and lower bounds for computatlonal complexlty. In short, a touch of computer sclence ls added to the fteld. To keep everythlng abstract, no tlmlngs or computer programs are lncluded. Thls was a Iabor of Iove. George Marsagl!a created CS690, a course on ran dom number generat!on at the School of Computer Sclence of McG!ll Unlverslty | ||
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Datensatz im Suchindex
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| author | Devroye, Luc |
| author_facet | Devroye, Luc |
| author_role | aut |
| author_sort | Devroye, Luc |
| author_variant | l d ld |
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| bvnumber | BV042420735 |
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| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.2 |
| dewey-search | 519.2 |
| dewey-sort | 3519.2 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4613-8643-8 |
| format | Electronic eBook |
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| id | DE-604.BV042420735 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:07Z |
| institution | BVB |
| isbn | 9781461386438 9781461386452 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027856152 |
| oclc_num | 1184736682 |
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| physical | 1 Online-Ressource (XVI, 843 p) |
| psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
| publishDate | 1986 |
| publishDateSearch | 1986 |
| publishDateSort | 1986 |
| publisher | Springer New York |
| record_format | marc |
| spelling | Devroye, Luc Verfasser aut Non-Uniform Random Variate Generation by Luc Devroye New York, NY Springer New York 1986 1 Online-Ressource (XVI, 843 p) txt rdacontent c rdamedia cr rdacarrier Thls text ls about one small fteld on the crossroads of statlstlcs, operatlons research and computer sclence. Statistleians need random number generators to test and compare estlmators before uslng them ln real l!fe. In operatlons research, random numbers are a key component ln !arge scale slmulatlons. Computer sclen tlsts need randomness ln program testlng, game playlng and comparlsons of algo rlthms. The appl!catlons are wlde and varled. Yet all depend upon the same com puter generated random numbers. Usually, the randomness demanded by an appl!catlon has some bullt-ln structure: typlcally, one needs more than just a sequence of Independent random blts or Independent uniform [0,1] random vari ables. Some users need random variables wlth unusual densltles, or random com blnatorlal objects wlth speclftc propertles, or random geometrlc objects, or ran dom processes wlth weil deftned dependence structures. Thls ls preclsely the sub ject area of the book, the study of non-uniform random varlates. The plot evolves around the expected complexlty of random varlate genera tlon algorlthms. We set up an ldeal!zed computatlonal model (wlthout overdolng lt), we lntroduce the notlon of unlformly bounded expected complexlty, and we study upper and lower bounds for computatlonal complexlty. In short, a touch of computer sclence ls added to the fteld. To keep everythlng abstract, no tlmlngs or computer programs are lncluded. Thls was a Iabor of Iove. George Marsagl!a created CS690, a course on ran dom number generat!on at the School of Computer Sclence of McG!ll Unlverslty Mathematics Distribution (Probability theory) Probability Theory and Stochastic Processes Mathematik Zufallsgenerator (DE-588)4191097-7 gnd rswk-swf Zufallszahlen (DE-588)4124968-9 gnd rswk-swf Stochastische Erzeugung (DE-588)4441717-2 gnd rswk-swf Zufallszahlen (DE-588)4124968-9 s Stochastische Erzeugung (DE-588)4441717-2 s 1\p DE-604 Zufallsgenerator (DE-588)4191097-7 s 2\p DE-604 https://doi.org/10.1007/978-1-4613-8643-8 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Devroye, Luc Non-Uniform Random Variate Generation Mathematics Distribution (Probability theory) Probability Theory and Stochastic Processes Mathematik Zufallsgenerator (DE-588)4191097-7 gnd Zufallszahlen (DE-588)4124968-9 gnd Stochastische Erzeugung (DE-588)4441717-2 gnd |
| subject_GND | (DE-588)4191097-7 (DE-588)4124968-9 (DE-588)4441717-2 |
| title | Non-Uniform Random Variate Generation |
| title_auth | Non-Uniform Random Variate Generation |
| title_exact_search | Non-Uniform Random Variate Generation |
| title_full | Non-Uniform Random Variate Generation by Luc Devroye |
| title_fullStr | Non-Uniform Random Variate Generation by Luc Devroye |
| title_full_unstemmed | Non-Uniform Random Variate Generation by Luc Devroye |
| title_short | Non-Uniform Random Variate Generation |
| title_sort | non uniform random variate generation |
| topic | Mathematics Distribution (Probability theory) Probability Theory and Stochastic Processes Mathematik Zufallsgenerator (DE-588)4191097-7 gnd Zufallszahlen (DE-588)4124968-9 gnd Stochastische Erzeugung (DE-588)4441717-2 gnd |
| topic_facet | Mathematics Distribution (Probability theory) Probability Theory and Stochastic Processes Mathematik Zufallsgenerator Zufallszahlen Stochastische Erzeugung |
| url | https://doi.org/10.1007/978-1-4613-8643-8 |
| work_keys_str_mv | AT devroyeluc nonuniformrandomvariategeneration |