LEADER 05494nam  2201261   450 
001 9910823944403321
005 20200520144314.0
010   $a1-4008-4063-5
024 7 $a10.1515/9781400840632
035   $a(CKB)2670000000139868
035   $a(EBL)832068
035   $a(OCoLC)769927219
035   $a(SSID)ssj0000593432
035   $a(PQKBManifestationID)11381906
035   $a(PQKBTitleCode)TC0000593432
035   $a(PQKBWorkID)10741466
035   $a(PQKB)10613464
035   $a(StDuBDS)EDZ0000515072
035   $a(DE-B1597)448013
035   $a(OCoLC)979582576
035   $a(DE-B1597)9781400840632
035   $a(Au-PeEL)EBL832068
035   $a(CaPaEBR)ebr10862955
035   $a(CaONFJC)MIL597392
035   $a(MiAaPQ)EBC832068
035   $a(EXLCZ)992670000000139868
100   $a20110908h20122012  uy|            0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aSpatiotemporal data analysis /$fGidon Eshel
205   $aCourse Book
210  1$aPrinceton :$cPrinceton University Press,$d[2012]
210  4$dİ2012
215   $a1 online resource (336 p.)
300   $aDescription based upon print version of record.
311   $a0-691-12891-X 
320   $aIncludes bibliographical references and index.
327   $t Frontmatter -- $tContents -- $tPreface -- $tAcknowledgments -- $tPart 1. Foundations -- $tOne. Introduction and Motivation -- $tTwo. Notation and Basic Operations -- $tThree. Matrix Properties, Fundamental Spaces, Orthogonality -- $tFour. Introduction to Eigenanalysis -- $tFive. The Algebraic Operation of SVD -- $tPart 2. Methods of Data Analysis -- $tSix. The Gray World of Practical Data Analysis: An Introduction to Part 2 -- $tSeven. Statistics in Deterministic Sciences: An Introduction -- $tEight. Autocorrelation -- $tNine. Regression and Least Squares -- $tTen. The Fundamental Theorem of Linear Algebra -- $tEleven. Empirical Orthogonal Functions -- $tTwelve. The SVD Analysis of Two Fields -- $tThirteen. Suggested Homework -- $tIndex
330   $a"A severe thunderstorm morphs into a tornado that cuts a swath of destruction through Oklahoma. How do we study the storm's mutation into a deadly twister? Avian flu cases are reported in China. How do we characterize the spread of the flu, potentially preventing an epidemic? The way to answer important questions like these is to analyze the spatial and temporal characteristics--origin, rates, and frequencies--of these phenomena. This comprehensive text introduces advanced undergraduate students, graduate students, and researchers to the statistical and algebraic methods used to analyze spatiotemporal data in a range of fields, including climate science, geophysics, ecology, astrophysics, and medicine. Gidon Eshel begins with a concise yet detailed primer on linear algebra, providing readers with the mathematical foundations needed for data analysis. He then fully explains the theory and methods for analyzing spatiotemporal data, guiding readers from the basics to the most advanced applications. This self-contained, practical guide to the analysis of multidimensional data sets features a wealth of real-world examples as well as sample homework exercises and suggested exams"--$cProvided by publisher.
606   $aSpatial analysis (Statistics)
610   $aEOF analysis.
610   $aEOF.
610   $aGram?chmidt orthogonalization.
610   $aSVD analysis.
610   $aSVD.
610   $aastrophysics.
610   $aautocorrelation functions.
610   $aautocovariance.
610   $aautoregressive model.
610   $aclimate science.
610   $acolumn space.
610   $acovariability matrix.
610   $adata analysis.
610   $adata matrices.
610   $adegrees of freedom.
610   $adeterministic science.
610   $aecology.
610   $aeigen-decomposition.
610   $aeigen-techniques.
610   $aeigenanalysis.
610   $aeigenvalues.
610   $aempirical orthogonal functions.
610   $aempirical science.
610   $aempiricism.
610   $aexercises.
610   $aforward problem.
610   $ageophysics.
610   $ainverse problem.
610   $alinear algebra.
610   $alinear regression.
610   $amatrices.
610   $amatrix structure.
610   $amatrix.
610   $amedicine.
610   $amultidimensional data sets.
610   $amultidimensional data.
610   $anondeterministic phenomena.
610   $anull space.
610   $aphenomena.
610   $aprobability distribution.
610   $arow space.
610   $asingular value decomposition.
610   $aspatiotemporal data.
610   $aspectral representation.
610   $asquare matrices.
610   $astatistics.
610   $astochastic processes.
610   $asubjective decisions.
610   $atheoretical science.
610   $atime series.
610   $atimescale.
610   $atornado.
610   $avariables.
610   $avectors.
615  0$aSpatial analysis (Statistics)
676   $a519.5/36
686   $aSCI019000$aMAT002050$2bisacsh
700   $aEshel$b Gidon$f1958-$01678986
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910823944403321
996   $aSpatiotemporal data analysis$94046958
997   $aUNINA