Complex Data Modeling and Computationally Intensive Statistical Methods
Mantovan, Pietro; Secchi, Piercesare
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Description for Complex Data Modeling and Computationally Intensive Statistical Methods
Hardback. Selected from the conference "S.Co.2009: Complex Data Modeling and Computationally Intensive Methods for Estimation and Prediction," these 20 papers cover the latest in statistical methods and computational techniques for complex and high dimensional datasets. Series: Contributions to Statistics. Num Pages: 164 pages, biography. BIC Classification: PBT; UFM; UNF. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 11. Weight in Grams: 426.
Recentyearshaveseentheadventanddevelopmentofmanydevicesabletorecordand storeaneverincreasingamountofinformation. Thefastprogressofthesetechnologies is ubiquitousthroughoutall ?elds of science and applied contexts, ranging from medicine,biologyandlifesciences,toeconomicsandindustry. Thedataprovided bytheseinstrumentshavedifferentforms:2D-3Dimagesgeneratedbydiagnostic medicalscanners,computervisionorsatelliteremotesensing,microarraydataand genesets,integratedclinicalandadministrativedatafrompublichealthdatabases, realtimemonitoringdataofabio-marker,systemcontroldatasets. Allthesedata sharethecommoncharacteristicofbeingcomplexandoftenhighlydimensional. Theanalysisofcomplexandhighlydimensionaldataposesnewchallengesto thestatisticianandrequiresthedevelopmentofnovelmodelsandtechniques,fueling manyfascinatingandfastgrowingresearchareasofmodernstatistics. Anincomplete listincludes for example: functionaldata analysis, that deals with data having a functionalnature,suchascurvesandsurfaces;shapeanalysisofgeometricforms,that relatestoshapematchingandshaperecognition,appliedtocomputationalvisionand medicalimaging;datamining,thatstudiesalgorithmsfortheautomaticextraction ofinformationfromdata,elicitingrulesandpatternsoutofmassivedatasets;risk analysis,fortheevaluationofhealth,environmental,andengineeringrisks;graphical models,thatallowproblemsinvolvinglarge-scalemodelswithmillionsofrandom variableslinkedincomplexwaystobeapproached;reliabilityofcomplexsystems, whoseevaluationrequirestheuseofmanystatisticalandprobabilistictools;optimal designofcomputersimulationstoreplaceexpensiveandtimeconsumingphysical experiments. Thecontributionspublishedinthisvolumearetheresultofaselectionbasedonthe presentations(aboutonehundred)givenattheconference"S. Co. 2009:Complexdata modelingandcomputationallyintensivemethodsforestimationandprediction",held ? atthePolitecnicodiMilano. S. Co. isaforumforthediscussionofnewdevelopments ? September14-16,2009. Thatof2009isitssixthedition,the?rstonebeingheldinVenice in1999. VI Preface andapplicationsofstatisticalmethodsandcomputationaltechniquesforcomplexand highlydimensionaldatasets. Thebookisaddressedtostatisticiansworkingattheforefrontofthestatistical analysisofcomplexandhighlydimensionaldataandoffersawidevarietyofstatistical models,computerintensivemethodsandapplications. Wewishtothankallassociateeditorsandrefereesfortheirvaluablecontributions thatmadethisvolumepossible. MilanandVenice,May2010 PietroMantovan PiercesareSecchi Contents Space-timetextureanalysisinthermalinfraredimagingforclassi?cation ofRaynaud'sPhenomenon GrazianoAretusi,LaraFontanella,LuigiIppolitiandArcangeloMerla...1 Mixed-effectsmodellingofKevlar?brefailuretimesthroughBayesian non-parametrics RaffaeleArgiento,AlessandraGuglielmiandAntonioPievatolo...13 Space?llingandlocallyoptimaldesignsforGaussianUniversalKriging AlessandroBaldiAntogniniandMaroussaZagoraiou...27 Exploitation,integrationandstatisticalanalysisofthePublicHealth DatabaseandSTEMIArchiveintheLombardiaregion PietroBarbieri,Niccolo'Grieco,FrancescaIeva,AnnaMariaPaganoniand PiercesareSecchi...41 Bootstrapalgorithmsforvarianceestimationin PSsampling AlessandroBarbieroandFulviaMecatti...5 7 FastBayesianfunctionaldataanalysisofbasalbodytemperature JamesM. Ciera...71 AparametricMarkovchaintomodelage-andstate-dependentwear processes MassimilianoGiorgio,MaurizioGuidaandGianpaoloPulcini...85 CasestudiesinBayesiancomputationusingINLA SaraMartinoandHav ? ardRue...99 Agraphicalmodelsapproachforcomparinggenesets ... Read more
Recentyearshaveseentheadventanddevelopmentofmanydevicesabletorecordand storeaneverincreasingamountofinformation. Thefastprogressofthesetechnologies is ubiquitousthroughoutall ?elds of science and applied contexts, ranging from medicine,biologyandlifesciences,toeconomicsandindustry. Thedataprovided bytheseinstrumentshavedifferentforms:2D-3Dimagesgeneratedbydiagnostic medicalscanners,computervisionorsatelliteremotesensing,microarraydataand genesets,integratedclinicalandadministrativedatafrompublichealthdatabases, realtimemonitoringdataofabio-marker,systemcontroldatasets. Allthesedata sharethecommoncharacteristicofbeingcomplexandoftenhighlydimensional. Theanalysisofcomplexandhighlydimensionaldataposesnewchallengesto thestatisticianandrequiresthedevelopmentofnovelmodelsandtechniques,fueling manyfascinatingandfastgrowingresearchareasofmodernstatistics. Anincomplete listincludes for example: functionaldata analysis, that deals with data having a functionalnature,suchascurvesandsurfaces;shapeanalysisofgeometricforms,that relatestoshapematchingandshaperecognition,appliedtocomputationalvisionand medicalimaging;datamining,thatstudiesalgorithmsfortheautomaticextraction ofinformationfromdata,elicitingrulesandpatternsoutofmassivedatasets;risk analysis,fortheevaluationofhealth,environmental,andengineeringrisks;graphical models,thatallowproblemsinvolvinglarge-scalemodelswithmillionsofrandom variableslinkedincomplexwaystobeapproached;reliabilityofcomplexsystems, whoseevaluationrequirestheuseofmanystatisticalandprobabilistictools;optimal designofcomputersimulationstoreplaceexpensiveandtimeconsumingphysical experiments. Thecontributionspublishedinthisvolumearetheresultofaselectionbasedonthe presentations(aboutonehundred)givenattheconference"S. Co. 2009:Complexdata modelingandcomputationallyintensivemethodsforestimationandprediction",held ? atthePolitecnicodiMilano. S. Co. isaforumforthediscussionofnewdevelopments ? September14-16,2009. Thatof2009isitssixthedition,the?rstonebeingheldinVenice in1999. VI Preface andapplicationsofstatisticalmethodsandcomputationaltechniquesforcomplexand highlydimensionaldatasets. Thebookisaddressedtostatisticiansworkingattheforefrontofthestatistical analysisofcomplexandhighlydimensionaldataandoffersawidevarietyofstatistical models,computerintensivemethodsandapplications. Wewishtothankallassociateeditorsandrefereesfortheirvaluablecontributions thatmadethisvolumepossible. MilanandVenice,May2010 PietroMantovan PiercesareSecchi Contents Space-timetextureanalysisinthermalinfraredimagingforclassi?cation ofRaynaud'sPhenomenon GrazianoAretusi,LaraFontanella,LuigiIppolitiandArcangeloMerla...1 Mixed-effectsmodellingofKevlar?brefailuretimesthroughBayesian non-parametrics RaffaeleArgiento,AlessandraGuglielmiandAntonioPievatolo...13 Space?llingandlocallyoptimaldesignsforGaussianUniversalKriging AlessandroBaldiAntogniniandMaroussaZagoraiou...27 Exploitation,integrationandstatisticalanalysisofthePublicHealth DatabaseandSTEMIArchiveintheLombardiaregion PietroBarbieri,Niccolo'Grieco,FrancescaIeva,AnnaMariaPaganoniand PiercesareSecchi...41 Bootstrapalgorithmsforvarianceestimationin PSsampling AlessandroBarbieroandFulviaMecatti...5 7 FastBayesianfunctionaldataanalysisofbasalbodytemperature JamesM. Ciera...71 AparametricMarkovchaintomodelage-andstate-dependentwear processes MassimilianoGiorgio,MaurizioGuidaandGianpaoloPulcini...85 CasestudiesinBayesiancomputationusingINLA SaraMartinoandHav ? ardRue...99 Agraphicalmodelsapproachforcomparinggenesets ... Read more
Product Details
Format
Hardback
Publication date
2010
Publisher
Springer Verlag Italy
Number of pages
164
Condition
New
Series
Contributions to Statistics
Number of Pages
164
Place of Publication
Milan, Italy
ISBN
9788847013858
SKU
V9788847013858
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Mantovan, Pietro; Secchi, Piercesare
Pietro Mantovan has been Professor of Statistics since 1986 at the University Ca' Foscari of Venezia, Italy, where he has served as coordinator of research units, head of the Departement of Statistics, and Dean of the Faculty of Economics. He has written several articles, monographs and textbooks on classical and Bayesian methods for statistical inference. His recent research interests focus ... Read more
Reviews for Complex Data Modeling and Computationally Intensive Statistical Methods
From the reviews: “This volume will be useful for the researchers working in this area. I read a few papers and, all in all, the book seems to have good applications. … All the papers are well structured and consistent in style and presentations. Each paper begins with an abstract and ends with a list of references. … The ... Read more