LEADER 04093nam 2200697Ia 450 001 9910827728103321 005 20200520144314.0 010 $a9786612848971 010 $a9781119957584 010 $a1119957583 010 $a9781282848979 010 $a1282848976 010 $a9780470685853 010 $a0470685859 010 $a9780470685860 010 $a0470685867 035 $a(CKB)2670000000047185 035 $a(EBL)624664 035 $a(OCoLC)680314762 035 $a(SSID)ssj0000421753 035 $a(PQKBManifestationID)12182482 035 $a(PQKBTitleCode)TC0000421753 035 $a(PQKBWorkID)10412370 035 $a(PQKB)10055349 035 $a(MiAaPQ)EBC624664 035 $a(Perlego)1012466 035 $a(EXLCZ)992670000000047185 100 $a20100712d2011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aLarge-scale inverse problems and quantification of uncertainty /$fedited by Lorenz Biegler ... [et al.] 210 $aChichester, West Sussex $cWiley$d2011 215 $a1 online resource (390 p.) 225 1 $aWiley series in computational statistics 300 $aDescription based upon print version of record. 311 08$a9780470697436 311 08$a0470697431 320 $aIncludes bibliographical references and index. 327 $aLarge-Scale Inverse Problems and Quantification of Uncertainty; Index; Contents; List of Contributors; 1 Introduction; 2 A Primer of Frequentist and Bayesian Inference in Inverse Problems; 3 Subjective Knowledge or Objective Belief? An Oblique Look to Bayesian Methods; 4 Bayesian and Geostatistical Approaches to Inverse Problems; 5 Using the Bayesian Framework to Combine Simulations and Physical Observations for Statistical Inference; 6 Bayesian Partition Models for Subsurface Characterization 327 $a7 Surrogate and Reduced-Order Modeling: A Comparison of Approaches for Large-Scale Statistical Inverse Problems8 Reduced Basis Approximation and A Posteriori Error Estimation for Parametrized Parabolic PDEs: Application to Real-Time Bayesian Parameter Estimation; 9 Calibration and Uncertainty Analysis for Computer Simulations with Multivariate Output; 10 Bayesian Calibration of Expensive Multivariate Computer Experiments; 11 The Ensemble Kalman Filter and Related Filters; 12 Using the Ensemble Kalman Filter for History Matching and Uncertainty Quantification of Complex Reservoir Models 327 $a13 Optimal Experimental Design for the Large-Scale Nonlinear Ill-Posed Problem of Impedance Imaging14 Solving Stochastic Inverse Problems: A Sparse Grid Collocation Approach; 15 Uncertainty Analysis for Seismic Inverse Problems: Two Practical Examples; 16 Solution of Inverse Problems Using Discrete ODE Adjoints 330 $aThis book focuses on computational methods for large-scale statistical inverse problems and provides an introduction to statistical Bayesian and frequentist methodologies. Recent research advances for approximation methods are discussed, along with Kalman filtering methods and optimization-based approaches to solving inverse problems. The aim is to cross-fertilize the perspectives of researchers in the areas of data assimilation, statistics, large-scale optimization, applied and computational mathematics, high performance computing, and cutting-edge applications. The solution to large-scale 410 0$aWiley series in computational statistics. 606 $aBayesian statistical decision theory 606 $aInverse problems (Differential equations) 606 $aMathematical optimization 615 0$aBayesian statistical decision theory. 615 0$aInverse problems (Differential equations) 615 0$aMathematical optimization. 676 $a515/.357 701 $aBiegler$b Lorenz T$0619818 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910827728103321 996 $aLarge-scale inverse problems and quantification of uncertainty$93926417 997 $aUNINA