01779oam 2200469M 450 991071631780332120200213070630.9(CKB)5470000002520961(OCoLC)1066022854(OCoLC)995470000002520961(EXLCZ)99547000000252096120071213d1926 ua 0engurcn|||||||||txtrdacontentcrdamediacrrdacarrierBridge across the Mississippi River at Little Falls, Minn. March 31, 1926. -- Referred to the House Calendar and ordered to be printed[Washington, D.C.] :[U.S. Government Printing Office],1926.1 online resource (2 pages)House report / 69th Congress, 1st session. House ;no. 753[United States congressional serial set ] ;[serial no. 8532]Batch processed record: Metadata reviewed, not verified. Some fields updated by batch processes.FDLP item number not assigned.Bridge construction industryBridgesDesign and constructionBridgesLegislative amendmentsLegislative materials.lcgftBridge construction industry.BridgesDesign and construction.Bridges.Legislative amendments.Newton Walter H.1880-1941Republican (MN)1387986WYUWYUOCLCOOCLCQBOOK9910716317803321Bridge across the Mississippi River at Little Falls, Minn. March 31, 1926. -- Referred to the House Calendar and ordered to be printed3510524UNINA06751nam 2200721 a 450 991082599460332120251116134537.097811184418621118441869978129918731312991873159781118441893111844189397811184418861118441885(CKB)2670000000325818(EBL)1120823(OCoLC)827207531(SSID)ssj0000801033(PQKBManifestationID)11431339(PQKBTitleCode)TC0000801033(PQKBWorkID)10773686(PQKB)11464339(MiAaPQ)EBC1120823(Perlego)1012534(EXLCZ)99267000000032581820120904d2013 uy 0engur|n|---|||||txtccrSpatio-temporal design advances in efficient data acquisition /edited by Jorge Mateu, Werner G. MullerChichester, West Sussex, U.K. Wiley20131 online resource (379 p.)Statistics in practiceDescription based upon print version of record.9780470974292 047097429X Includes bibliographical references and index.Spatio-temporal design; Contents; Contributors; Foreword; Chapter 1 Collecting spatio-temporal data; 1.1 Introduction; 1.2 Paradigms in spatio-temporal design; 1.3 Paradigms in spatio-temporal modeling; 1.4 Geostatistics and spatio-temporal random functions; 1.4.1 Relevant spatio-temporal concepts; 1.4.2 Properties of the spatio-temporal covariance and variogram functions; 1.4.3 Spatio-temporal kriging; 1.4.4 Spatio-temporal covariance models; 1.4.5 Parametric estimation of spatio-temporal covariograms; 1.5 Types of design criteria and numerical optimization1.6 The problem set: Upper Austria1.6.1 Climatic data; 1.6.2 Grassland usage; 1.7 The chapters; Acknowledgments; References; Chapter 2 Model-based frequentist design for univariate and multivariate geostatistics; 2.1 Introduction; 2.2 Design for univariate geostatistics; 2.2.1 Data-model framework; 2.2.2 Design criteria; 2.2.3 Algorithms; 2.2.4 Toy example; 2.3 Design for multivariate geostatistics; 2.3.1 Data-model framework; 2.3.2 Design criteria; 2.3.3 Toy example; 2.4 Application: Austrian precipitation data network; 2.5 Conclusions; ReferencesChapter 3 Model-based criteria heuristics for second-phase spatial sampling3.1 Introduction; 3.2 Geometric and geostatistical designs; 3.2.1 Efficiency of spatial sampling designs; 3.2.2 Sampling spatial variables in a geostatistical context; 3.2.3 Sampling designs minimizing the kriging variance; 3.3 Augmented designs: Second-phase sampling; 3.3.1 Additional sampling schemes to maximize change in the kriging variance; 3.3.2 A weighted kriging variance approach; 3.4 A simulated annealing approach; 3.5 Illustration; 3.5.1 Initial sampling designs; 3.5.2 Augmented designs; 3.6 DiscussionReferencesChapter 4 Spatial sampling design by means of spectral approximations to the error process; 4.1 Introduction; 4.2 A brief review on spatial sampling design; 4.3 The spatial mixed linear model; 4.4 Classical Bayesian experimental design problem; 4.5 The Smith and Zhu design criterion; 4.6 Spatial sampling design for trans-Gaussian kriging; 4.7 The spatDesign toolbox; 4.7.1 Covariance estimation and variography software; 4.7.2 Spatial interpolation and kriging software; 4.7.3 Spatial sampling design software; 4.8 An example session; 4.8.1 Preparatory calculations4.8.2 Optimal design for the BSLM4.8.3 Design for the trans-Gaussian kriging; 4.9 Conclusions; References; Chapter 5 Entropy-based network design using hierarchical Bayesian kriging; 5.1 Introduction; 5.2 Entropy-based network design using hierarchical Bayesian kriging; 5.3 The data; 5.4 Spatio-temporal modeling; 5.5 Obtaining a staircase data structure; 5.6 Estimating the hyperparameters Hg and the spatial correlations between gauge stations; 5.7 Spatial predictive distribution over the 445 areas located in the 18 districts of Upper Austria5.8 Adding gauge stations over the 445 areas located in the 18 districts of Upper Austria"A state-of-the-art presentation of optimum spatio-temporal sampling design - bridging classic ideas with modern statistical modeling concepts and the latest computational methods.Spatio-temporal Design presents a comprehensive state-of-the-art presentation combining both classical and modern treatments of network design and planning for spatial and spatio-temporal data acquisition. A common problem set is interwoven throughout the chapters, providing various perspectives to illustrate a complete insight to the problem at hand.Motivated by the high demand for statistical analysis of data that takes spatial and spatio-temporal information into account, this book incorporates ideas from the areas of time series, spatial statistics and stochastic processes, and combines them to discuss optimum spatio-temporal sampling design.Spatio-temporal Design: Advances in Efficient Data Acquisition: Provides an up-to-date account of how to collect space-time data for monitoring, with a focus on statistical aspects and the latest computational methods Discusses basic methods and distinguishes between design and model-based approaches to collecting space-time data. Features model-based frequentist design for univariate and multivariate geostatistics, and second-phase spatial sampling. Integrates common data examples and case studies throughout the book in order to demonstrate the different approaches and their integration. Includes real data sets, data generating mechanisms and simulation scenarios. Accompanied by a supporting website featuring R code. Spatio-temporal Design presents an excellent book for graduate level students as well as a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences"--Provided by publisher.Statistics in PracticeSampling (Statistics)Spatial analysis (Statistics)Sampling (Statistics)Spatial analysis (Statistics)001.4/33MAT029000bisacshMateu Jorge1624718Müller W. G(Werner G.)1624719MiAaPQMiAaPQMiAaPQBOOK9910825994603321Spatio-temporal design3959869UNINA