Random Fields Spatial Data by Hristopulos Dionissios (16 results)
- Hardcover
Seller: California Books, Miami, FL, U.S.A.California Books
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- Hardcover
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Hardcover. Condition: New.
- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Hardcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Hardcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Hardcover
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
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Hardback. Condition: New. 2020 ed. This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoretical framework for the development of spa…tial models and their applications in data analysis. The contents of the book include topics from classical statistics and random field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model inference, kriging-based prediction) and statistical physics (fractals, Ising model, simulated annealing, maximum entropy, functional integral representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processes and neural networks used in machine learning. Connections with applied mathematics are highlighted by means ofmodels based on stochastic partial differential equations. An interlude on autoregressive time series provides useful lower-dimensional analogies and a connection with the classical linear harmonic oscillator. Other chapters focus on non-Gaussian random fields and stochastic simulation methods. The book also presents results based on the author's research on Spartan random fields that were inspired by statistical field theories originating in physics. The equivalence of the one-dimensional Spartan random field model with the classical, linear, damped harmonic oscillator driven by white noise is highlighted. Ideas with potentially significant computational gains for the processing of big spatial data are presented and discussed. The final chapter concludes with a description of the Karhunen-Loève expansion of the Spartan model. The book will appeal to engineers, physicists, and geoscientists whose research involves spatial models or spatialdata analysis. Anyone with background in probability and statistics can read at least parts of the book. Some chapters will be easier to understand by readers familiar with differential equations and Fourier transforms.
- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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- Hardcover
Seller: moluna, Greven, Germanymoluna
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£ 128.68
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Condition: New. Provides a bridge between statistical physics and spatial statistics and underlines links between geostatistics, applied mathematics and machine learningPresents a unique approach, developed by the author, which has strong potential for fast .
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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£ 128.23
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoreti…cal framework for the development of spatial models and their applications in data analysis.The contents of the book include topics from classical statistics and random field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model inference, kriging-based prediction) and statistical physics (fractals, Ising model, simulated annealing, maximum entropy, functional integral representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processesand neural networksused in machine learning. Connections with applied mathematics are highlighted by means ofmodels based on stochastic partial differential equations. An interlude on autoregressive time series provides useful lower-dimensional analogiesand a connection with the classical linear harmonic oscillator. Other chapters focus on non-Gaussian random fields and stochastic simulation methods. The book also presents results based on the author's research on Spartan random fields that were inspired by statistical field theories originating in physics. Theequivalence of the one-dimensional Spartan random field model with the classical, linear, damped harmonic oscillator driven by white noise is highlighted. Ideas with potentially significant computational gains for the processing of big spatial data are presented and discussed. The final chapter concludes with a description of the Karhunen-Loève expansion of the Spartan model.The book will appeal to engineers, physicists, and geoscientists whose research involves spatial models or spatialdata analysis. Anyone withbackgroundin probability and statistics can read at least parts of the book.Some chapters will be easier to understand by readers familiar with differential equations and Fourier transforms.
- Hardcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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£ 151.09
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Hardback. Condition: New. 2020 ed. This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a general theoretical framework for the development of spa…tial models and their applications in data analysis. The contents of the book include topics from classical statistics and random field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model inference, kriging-based prediction) and statistical physics (fractals, Ising model, simulated annealing, maximum entropy, functional integral representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processes and neural networks used in machine learning. Connections with applied mathematics are highlighted by means ofmodels based on stochastic partial differential equations. An interlude on autoregressive time series provides useful lower-dimensional analogies and a connection with the classical linear harmonic oscillator. Other chapters focus on non-Gaussian random fields and stochastic simulation methods. The book also presents results based on the author's research on Spartan random fields that were inspired by statistical field theories originating in physics. The equivalence of the one-dimensional Spartan random field model with the classical, linear, damped harmonic oscillator driven by white noise is highlighted. Ideas with potentially significant computational gains for the processing of big spatial data are presented and discussed. The final chapter concludes with a description of the Karhunen-Loève expansion of the Spartan model. The book will appeal to engineers, physicists, and geoscientists whose research involves spatial models or spatialdata analysis. Anyone with background in probability and statistics can read at least parts of the book. Some chapters will be easier to understand by readers familiar with differential equations and Fourier transforms.
- Hardcover
- Print on Demand
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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£ 97.36
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Condition: new. Questo è un articolo print on demand.
- Hardcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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£ 122.81
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a…general theoretical framework for the development of spatial models and their applications in data analysis.The contents of the book include topics from classical statistics and random field theory (regression models, Gaussian random fields, stationarity, correlation functions) spatial statistics (variogram estimation, model inference, kriging-based prediction) and statistical physics (fractals, Ising model, simulated annealing, maximum entropy, functional integral representations, perturbation and variational methods). The book also explores links between random fields, Gaussian processesand neural networksused in machine learning. Connections with applied mathematics are highlighted by means ofmodels based on stochastic partial differential equations. An interlude on autoregressive time series provides useful lower-dimensional analogiesand a connection with the classical linear harmonic oscillator. Other chapters focus on non-Gaussian random fields and stochastic simulation methods. The book also presents results based on the author's research on Spartan random fields that were inspired by statistical field theories originating in physics. Theequivalence of the one-dimensional Spartan random field model with the classical, linear, damped harmonic oscillator driven by white noise is highlighted. Ideas with potentially significant computational gains for the processing of big spatial data are presented and discussed. The final chapter concludes with a description of the Karhunen-Loève expansion of the Spartan model.The book will appeal to engineers, physicists, and geoscientists whose research involves spatial models or spatialdata analysis. Anyone withbackgroundin probability and statistics can read at least parts of the book.Some chapters will be easier to understand by readers familiar with differential equations and Fourier transforms. 900 pp. Englisch.
- Hardcover
- Print on Demand
Seller: preigu, Osnabrück, Germanypreigu
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£ 105.91
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Buch. Condition: Neu. Random Fields for Spatial Data Modeling | A Primer for Scientists and Engineers | Dionissios T. Hristopulos | Buch | Advances in Geographic Information Science | xxx | Englisch | 2020 | Springer | EAN 9789402419160 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelber…g, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
- Hardcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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£ 167.79
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- Hardcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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£ 122.81
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides an inter-disciplinary introduction to the theory of random fields and its applications. Spatial models and spatial data analysis are integral parts of many scientific and engineering disciplines. Random fields provide a gene…ral theoretical framework for the development of spatial models and their applications in data analysis.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 900 pp. Englisch.
- Hardcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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£ 179.15
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Condition: New. PRINT ON DEMAND.
