LEADER 02863oam 2200601I 450 001 9910541773603321 005 20200520144314.0 010 $a0-429-18481-6 010 $a1-4398-8275-4 024 7 $a10.1201/9781439882757 035 $a(CKB)3710000000391598 035 $a(EBL)1648265 035 $a(SSID)ssj0001460159 035 $a(PQKBManifestationID)12590141 035 $a(PQKBTitleCode)TC0001460159 035 $a(PQKBWorkID)11465645 035 $a(PQKB)10003536 035 $a(MiAaPQ)EBC1648265 035 $a(CaSebORM)9781439882757 035 $a(Au-PeEL)EBL1648265 035 $a(CaPaEBR)ebr11167511 035 $a(OCoLC)908079346 035 $a(EXLCZ)993710000000391598 100 $a20180706h20102011 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aTime series $emodeling, computation, and inference /$fby Raquel Prado and Mike West 205 $a1st edition 210 1$aBoca Raton, FL :$cChapman and Hall/CRC, an imprint of Taylor and Francis,$d[2010]. 210 4$dİ2011 215 $a1 online resource (375 p.) 225 1 $aChapman & Hall/CRC texts in Statistical Science Series 300 $a"A Chapman & Hall Book." 311 $a1-4200-9336-3 320 $aIncludes bibliographical references and indexes. 327 $aFront cover; Contents; Preface; Chapter 1: Notation, definitions, and basic inference; Chapter 2: Traditional time domain models; Chapter 3: The frequency domain; Chapter 4: Dynamic linear models; Chapter 5: State-space TVAR models; Chapter 6: General state-space models andsequential Monte Carlo methods; Chapter 7: Mixture models in time series; Chapter 8: Topics and examples in multipletime series; Chapter 9: Vector AR and ARMA models; Chapter 10: Multivariate DLMs and covariance models; Bibliography; Author Index; Subject Index; Back cover 330 3 $aFocusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. 410 0$aTexts in statistical science. 606 $aTime-series analysis$vTextbooks 608 $aElectronic books. 615 0$aTime-series analysis 676 $a519.5/5 700 $aPrado$b Raquel$0614671 702 $aWest$b Mike 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910541773603321 996 $aTime series$92746388 997 $aUNINA LEADER 01696aam 2200421I 450 001 9910710524303321 005 20130111102445.0 024 8 $aGOVPUB-C13-e64ef5bd34abb62c5d84673244f58f84 035 $a(CKB)5470000002478057 035 $a(OCoLC)823930616 035 $a(EXLCZ)995470000002478057 100 $a20130111d2009 ua 0 101 0 $aeng 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aThermodynamic evaluation of the propensity of niobium to absorb hydrogen during fabrication of superconducting radio frequency accelerator cavities /$fRichard E. Ricker 210 1$aGaithersburg, MD :$cU.S. Dept. of Commerce, National Institute of Standards and Technology,$d2009. 215 $a1 online resource (27 pages) $cillustrations (some color) 225 1 $aNISTIR ;$v7635 300 $aContributed record: Metadata reviewed, not verified. Some fields updated by batch processes. 300 $aOctober 2, 2009. 300 $aTitle from title screen (viewed January 13, 2013). 320 $aIncludes bibliographical references. 606 $aCorrosion and anti-corrosives 606 $aNiobium 615 0$aCorrosion and anti-corrosives. 615 0$aNiobium. 700 $aRicker$b Richard E$01393557 701 $aRicker$b Richard E$01393557 712 02$aNational Institute of Standards and Technology (U.S.) 801 0$bNBS 801 1$bNBS 801 2$bGPO 906 $aBOOK 912 $a9910710524303321 996 $aThermodynamic evaluation of the propensity of niobium to absorb hydrogen during fabrication of superconducting radio frequency accelerator cavities$93452304 997 $aUNINA