The Uncertainty Analysis of Model Results : : A Practical Guide
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Language:  English 
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Cham : : Springer International Publishing : : Imprint: Springer,,
2018

Edition:  1st ed. 2018. 
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Online Access:  https://doi.org/10.1007/9783319762975 
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opacEUL01000979410 

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ebook 
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Hofer, Eduard. szerző aut http://id.loc.gov/vocabulary/relators/aut The Uncertainty Analysis of Model Results : A Practical Guide by Eduard Hofer. 1st ed. 2018. Cham : Springer International Publishing : Imprint: Springer, 2018 XV, 346 p. 129 illus., 107 illus. in color. online forrás szöveg txt rdacontent számítógépes c rdamedia távoli hozzáférés cr rdacarrier szövegfájl PDF rda Preface  Introduction and necessary distinctions  Step 1: Search  Step 2: Quantify  Step 3: Propagate  Step 4: Estimate uncertainty  Step 5: Rank uncertainties  Step 6: Present the analysis and interpret its results  Practical execution of the analysis  Uncertainty analysis when separation of uncertainties is required  Practical examples  References  Subject index. This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decisionmakers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results. Nyomtatott kiadás: ISBN 9783319762968 Nyomtatott kiadás: ISBN 9783319762982 Nyomtatott kiadás: ISBN 9783030094560 Az ekönyvek a teljes ELTE IPtartományon belül online elérhetők. könyv ebook Mathematical statistics. EUL10000079757 Y Computer simulation. EUL10000093376 Y Economic theory. EUL10001044656 Y Environmental sciences. EUL10001072417 Y System safety. EUL10001074773 Y Statistical Theory and Methods. Simulation and Modeling. Mathematical Modeling and Industrial Mathematics. Economic Theory/Quantitative Economics/Mathematical Methods. Math. Appl. in Environmental Science. Quality Control, Reliability, Safety and Risk. elektronikus könyv SpringerLink (Online service) közreadó testület Online változat https://doi.org/10.1007/9783319762975 EUL01 
language 
English 
format 
Book 
author 
Hofer, Eduard., szerző 
spellingShingle 
Hofer, Eduard., szerző The Uncertainty Analysis of Model Results : A Practical Guide Mathematical statistics. Computer simulation. Economic theory. Environmental sciences. System safety. Statistical Theory and Methods. Simulation and Modeling. Mathematical Modeling and Industrial Mathematics. Economic Theory/Quantitative Economics/Mathematical Methods. Math. Appl. in Environmental Science. Quality Control, Reliability, Safety and Risk. elektronikus könyv 
author_facet 
Hofer, Eduard., szerző SpringerLink (Online service), közreadó testület 
author_corporate 
SpringerLink (Online service), közreadó testület 
author_sort 
Hofer, Eduard. 
title 
The Uncertainty Analysis of Model Results : A Practical Guide 
title_sub 
A Practical Guide 
title_short 
The Uncertainty Analysis of Model Results : 
title_full 
The Uncertainty Analysis of Model Results : A Practical Guide by Eduard Hofer. 
title_fullStr 
The Uncertainty Analysis of Model Results : A Practical Guide by Eduard Hofer. 
title_full_unstemmed 
The Uncertainty Analysis of Model Results : A Practical Guide by Eduard Hofer. 
title_auth 
The Uncertainty Analysis of Model Results : A Practical Guide 
title_sort 
uncertainty analysis of model results a practical guide 
publishDate 
2018 
publishDateSort 
2018 
physical 
XV, 346 p. 129 illus., 107 illus. in color. : online forrás 
edition 
1st ed. 2018. 
isbn 
9783319762975 
callnumberfirst 
Q  Science 
callnumbersubject 
QA  Mathematics 
callnumberlabel 
QA276280 
callnumberraw 
979410 
callnumbersearch 
979410 
topic 
Mathematical statistics. Computer simulation. Economic theory. Environmental sciences. System safety. Statistical Theory and Methods. Simulation and Modeling. Mathematical Modeling and Industrial Mathematics. Economic Theory/Quantitative Economics/Mathematical Methods. Math. Appl. in Environmental Science. Quality Control, Reliability, Safety and Risk. elektronikus könyv 
topic_facet 
Mathematical statistics. Computer simulation. Economic theory. Environmental sciences. System safety. Statistical Theory and Methods. Simulation and Modeling. Mathematical Modeling and Industrial Mathematics. Economic Theory/Quantitative Economics/Mathematical Methods. Math. Appl. in Environmental Science. Quality Control, Reliability, Safety and Risk. elektronikus könyv Mathematical statistics. Computer simulation. Economic theory. Environmental sciences. System safety. Statistical Theory and Methods. Simulation and Modeling. Mathematical Modeling and Industrial Mathematics. Economic Theory/Quantitative Economics/Mathematical Methods. Math. Appl. in Environmental Science. Quality Control, Reliability, Safety and Risk. 
url 
https://doi.org/10.1007/9783319762975 
illustrated 
Not Illustrated 
deweyhundreds 
500  Science 
deweytens 
510  Mathematics 
deweyones 
519  Probabilities & applied mathematics 
deweyfull 
519.5 
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3519.5 
deweyraw 
519.5 
deweysearch 
519.5 
first_indexed 
20231226T23:12:44Z 
last_indexed 
20231229T19:17:07Z 
recordtype 
opac 
publisher 
Cham : : Springer International Publishing : : Imprint: Springer, 
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1786641203555467264 
score 
13,368518 
generalnotes 
This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decisionmakers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results. 