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| 001 | 978-3-540-45987-3 | ||
| 003 | DE-He213 | ||
| 005 | 20190213151754.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 121227s1988 gw | s |||| 0|eng d | ||
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_a9783540459873 _9978-3-540-45987-3 |
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| 024 | 7 |
_a10.1007/BFb0079792 _2doi |
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| 050 | 4 | _aQA297-299.4 | |
| 072 | 7 |
_aPBKS _2bicssc |
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_aMAT021000 _2bisacsh |
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| 072 | 7 |
_aPBKS _2thema |
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| 082 | 0 | 4 |
_a518 _223 |
| 100 | 1 |
_aNovak, Erich. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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| 245 | 1 | 0 |
_aDeterministic and Stochastic Error Bounds in Numerical Analysis _h[electronic resource] / _cby Erich Novak. |
| 264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c1988. |
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| 300 |
_aVIII, 124 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aLecture Notes in Mathematics, _x0075-8434 ; _v1349 |
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| 505 | 0 | _aContents: Introduction -- Deterministic Error Bounds -- Error Bounds for Monte Carlo Methods -- Average Error Bounds -- Appendix: Existence and Uniqueness of Optimal Algorithms -- Bibliography -- Notations -- Index. | |
| 520 | _aIn these notes different deterministic and stochastic error bounds of numerical analysis are investigated. For many computational problems we have only partial information (such as n function values) and consequently they can only be solved with uncertainty in the answer. Optimal methods and optimal error bounds are sought if only the type of information is indicated. First, worst case error bounds and their relation to the theory of n-widths are considered; special problems such approximation, optimization, and integration for different function classes are studied and adaptive and nonadaptive methods are compared. Deterministic (worst case) error bounds are often unrealistic and should be complemented by different average error bounds. The error of Monte Carlo methods and the average error of deterministic methods are discussed as are the conceptual difficulties of different average errors. An appendix deals with the existence and uniqueness of optimal methods. This book is an introduction to the area and also a research monograph containing new results. It is addressd to a general mathematical audience as well as specialists in the areas of numerical analysis and approximation theory (especially optimal recovery and information-based complexity). | ||
| 650 | 0 | _aNumerical analysis. | |
| 650 | 1 | 4 |
_aNumerical Analysis. _0http://scigraph.springernature.com/things/product-market-codes/M14050 |
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783662204672 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783540503682 |
| 830 | 0 |
_aLecture Notes in Mathematics, _x0075-8434 ; _v1349 |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1007/BFb0079792 |
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| 912 | _aZDB-2-LNM | ||
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