Sign-In
Cart
Modeling Spatio-Temporal Data: Markov Random Fields, Objective Bayes, and Multiscale Models
Hardcover
ISBN13: 9781032622095
Publisher: CRC Press
Published: Nov 29 2024
Pages: 276
Weight: 1.30
Height: 0.69 Width: 6.14 Depth: 9.21
Language: English
Several important topics in spatial and spatio-temporal statistics developed in the last 15 years have not received enough attention in textbooks. Modeling Spatio-Temporal Data: Markov Random Fields, Objectives Bayes, and Multiscale Models aims to fill this gap by providing an overview of a variety of recently proposed approaches for the analysis of spatial and spatio-temporal datasets, including proper Gaussian Markov random fields, dynamic multiscale spatio-temporal models, and objective priors for spatial and spatio-temporal models. The goal is to make these approaches more accessible to practitioners, and to stimulate additional research in these important areas of spatial and spatio-temporal statistics.
Key topics:
- Proper Gaussian Markov random fields and their uses as building blocks for spatio-temporal models and multiscale models.
- Hierarchical models with intrinsic conditional autoregressive priors for spatial random effects, including reference priors, results on fast computations, and objective Bayes model selection.
- Objective priors for state-space models and a new approximate reference prior for a spatio-temporal model with dynamic spatio-temporal random effects.
- Spatio-temporal models based on proper Gaussian Markov random fields for Poisson observations.
- Dynamic multiscale spatio-temporal thresholding for spatial clustering and data compression.
- Multiscale spatio-temporal assimilation of computer model output and monitoring station data.
- Dynamic multiscale heteroscedastic multivariate spatio-temporal models.
- The M-open multiple optima paradox and some of its practical implications for multiscale modeling.
- Ensembles of dynamic multiscale spatio-temporal models for smooth spatio-temporal processes.
The audience for this book are practitioners, researchers, and graduate students in statistics, data science, machine learning, and related fields. Prerequisites for this book are master's-level courses on statistical inference, linear models, and Bayesian statistics. This book can be used as a textbook for a special topics course on spatial and spatio-temporal statistics, as well as supplementary material for graduate courses on spatial and spatio-temporal modeling.
Also from
Ferreira, Marco A. R.
Time Series: Modeling, Computation, and Inference, Second Edition
Ferreira, Marco A. R.
West, Mike
Prado, Raquel
Hardcover
Time Series: Modeling, Computation, and Inference, Second Edition
Prado, Raquel
Ferreira, Marco A. R.
West, Mike
Paperback
Also in
Probability & Statistics
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Wickham, Hadley
Grolemund, Garrett
Paperback
AP Statistics Premium, 2027: 9 Practice Tests + Comprehensive Review + Online Practice
Sternstein, Martin, PH. D.
Paperback
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Cetinkaya-Rundel, Mine
Wickham, Hadley
Grolemund, Garrett
Paperback
Graph Paper Composition Notebook: Quad Ruled 5x5, Grid Paper for Students in Math and Science
Wizo, Math
Paperback
Stat 208 Statistical Thinking: A Book for Stat 208 at Virginia Commonwealth University
Street IV, W. Scott
Durfee, Becky
Paperback
Forecasting: Principles and Practice, the Pythonic Way
Athanasopoulos, George
Hyndman, Rob J.
Paperback
The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck
Spiegelhalter, David
Paperback
Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries
Frost, Jim
Paperback
Mastering Claude AI: Practical Journey from First Prompts to Pro with Claude AI
Dickey, Ryan
Paperback
The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck
Spiegelhalter, David
Hardcover
How the World Really Works: The Science Behind How We Got Here and Where We're Going
Smil, Vaclav
Paperback
Ai-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Bruce, Peter
Bruce, Andrew
Gedeck, Peter
Paperback
Scale: The Universal Laws of Life, Growth, and Death in Organisms, Cities, and Companies
West, Geoffrey
Paperback
The Random Universe: How Models and Probability Help Us Make Sense of the Cosmos
Jaffe, Andrew H.
Hardcover
An Introduction to Statistical Learning: With Applications in R
Witten, Daniela
Hastie, Trevor
James, Gareth
Paperback
Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results
Hatcher, Larry
Paperback
Schaum's Outline of Probability and Statistics, 4th Edition: 897 Solved Problems + 20 Videos
Spiegel, Murray R.
Schiller, John J.
Srinivasan, R. Alu
Paperback
The Only Math Book You'll Ever Need, Revised Edition: Hundreds of Easy Solutions and Shortcuts for Mastering Everyday Numbers
Heller, Barbara R.
Kogelman, Stanley
Paperback
Mathematical Foundations of Quantum Computing: A Scaffolding Approach
Yu, James
Cheng, Ran
Lee, Peter
Hardcover
Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, Second Edition
Winston, Wayne L.
Nestler, Scott
Pelechrinis, Konstantinos
Paperback
Schaum's Outline of Probability, Random Variables, and Random Processes, Fourth Edition
Hsu, Hwei P.
Paperback
SQL Server 2025 Unveiled: The Ai-Ready Enterprise Database with Microsoft Fabric Integration
Ward, Bob
Paperback
How the World Really Works: The Science Behind How We Got Here and Where We're Going
Smil, Vaclav
Hardcover
Building Large Language Models from Scratch: Design, Train, and Deploy Llms with Pytorch
Grigorov, Dilyan
Paperback
Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis
Harrell Jr, Frank E.
Paperback
Challenging Mathematical Problems with Elementary Solutions, Vol. I: Volume 1
Yaglom, A. M.
Yaglom, I. M.
Paperback
Quantum Computing and Quantum Machine Learning for Engineers and Developers
Fraser, Roydon Andrew
Van Griensven Thé, Jesse
Rosas-Bustos, Jose
Hardcover
Making ChatGPT Work for You: Getting the Most Out of Generative AI as a Non-Techie
Evelyn, Lydia
Paperback
Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Downey, Allen B.
Paperback
Probably the Best Book on Statistics Ever Written: How to Beat the Odds and Make Better Decisions
Shapira, Haim
Hardcover
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
Domingos, Pedro
Paperback
Databricks Data Intelligence Platform: Unlocking the Genai Revolution
Gupta, Nikhil
Yip, Jason
Paperback
The End of Average: Unlocking Our Potential by Embracing What Makes Us Different
Rose, Todd
Paperback
Large Language Models: A Deep Dive: Bridging Theory and Practice
Keenan, Kevin
Somers, Garrett
Kamath, Uday
Hardcover
Scorecasting: The Hidden Influences Behind How Sports Are Played and Games Are Won
Moskowitz, Tobias
Wertheim, L. Jon
Paperback
Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Downey, Allen B.
Hardcover
AI for Robotics: Toward Embodied and General Intelligence in the Physical World
Gopalakrishnan, Keerthana
Imran, Alishba
Paperback
Time Series Analysis and Its Applications: With R Examples
Shumway, Robert H.
Stoffer, David S.
Hardcover
Guide to Methods for Students of Political Science: Property, Proof, and Dispute in Catalonia Around the Year 1000
Van Evera, Stephen
Paperback
Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI
Raschka, Sebastian
Paperback
An Introduction to Statistical Learning: With Applications in Python
Witten, Daniela
Hastie, Trevor
James, Gareth
Hardcover
Learning Statistics with Jamovi: A Tutorial for Beginners in Statistical Analysis
Navarro, Danielle
Foxcroft, David
Paperback
A Modern Introduction to Probability and Statistics: Understanding Why and How
Lopuhaä, H. P.
Dekking, F. M.
Kraaikamp, C.
Hardcover
The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of C
McGrayne, Sharon Bertsch
Paperback
Observability for Large Language Models: Site Reliability and Chaos Engineering for AI at Scale
Sharma, Ankush
Paperback
Building Generative AI Agents: Using Langgraph, Autogen, and Crewai
Deshmukh, Gaurav
Taulli, Tom
Paperback
Challenging Mathematical Problems with Elementary Solutions, Vol. II: Volume 2
Yaglom, A. M.
Yaglom, I. M.
Paperback
High-Dimensional Probability: An Introduction with Applications in Data Science
Vershynin, Roman
Hardcover
Modern Time Series Forecasting with Python - Second Edition: Industry-ready machine learning and deep learning time series analysis with PyTorch and p
Joseph, Manu
Tackes, Jeffrey
Paperback
Mathematical Foundations of Quantum Computing: A Scaffolding Approach
Yu, James
Cheng, Ran
Lee, Peter
Paperback
The ESRI Guide to GIS Analysis, Volume 2: Spatial Measurements and Statistics
Griffin, Lauren Scott
Mitchell, Andy
Paperback
Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin
Adam, John a.
Weinstein, Lawrence
Paperback
Unlocking Dbt: Design and Deploy Transformations in Your Cloud Data Warehouse
Cyr, Cameron
Dorsey, Dustin
Paperback
Prompt Engineering for Everyone: A Self-Taught, Human-Centered Approach to AI Programming
Tavakoli, Hamid
Paperback
The Design Inference: Eliminating Chance through Small Probabilities
Dembski, William A.
Ewert, Winston
Hardcover
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
Tibshirani, Robert
Friedman, Jerome
Hastie, Trevor
Hardcover
System Design with AI Interview Guide: Designing Scalable, Agentic, and Defensible Systems
Bhardwaj, Rohit
Paperback
Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists
Best, Joel
Hardcover
Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries
Frost, Jim
Hardcover
ACCUPLACER Math Prep: ACCUPLACER Math Test Study Guide with Two Practice Tests [Includes Detailed Answer Explanations]
Tpb Publishing
Paperback
Deep Learning in Computational Mechanics: An Introductory Course
Herrmann, Leon
Weeger, Oliver
Jokeit, Moritz
Hardcover
An Introduction to Statistical Learning: With Applications in Python
Witten, Daniela
Hastie, Trevor
James, Gareth
Paperback
Large Language Model Recipes: A Hands-On Guide to Fine-Tuning, Optimization, Deployment, and Real-World Applications
Kaata, Sashi Kiran
Bolla, Bharath Kumar
Subbaiah, Kalpa
Paperback
Bayesian Analysis with Python - Third Edition: A practical guide to probabilistic modeling
Martin, Osvaldo
Paperback
Enterprise Guide for Implementing Generative AI and Agentic AI: A Practical Guide to Developing, Deploying, and Operationalizing Ai-Driven Application
Edward, Shakuntala Gupta
Bhattacharya, Rahul
Sinha, Vikas
Paperback
From Data to Dollars: Getting Started with Data Analytics and AI in Startups
Sidoruk, Piotr
Paperback
Large Language Models: From Theory to Production
Pacheco Aznar, David
Vanegas, Esteban
Noguer I. Alonso, Miquel
Paperback
The Practical Guide to Large Language Models: Hands-On AI Applications with Hugging Face Transformers
Gridin, Ivan
Paperback
The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day
Hand, David J.
Paperback
Practical Generative Ai: From Concept to Deployment: Building and Deploying Ethical AI-Powered Solutions
Singh, Pramod
McKeone, James
Paperback
Making Statistics Work: Information Theory and Bayesian Inference
Foley, Duncan
Scharfenaker, Ellis
Paperback
Databricks Data Intelligence Platform: Powering the Agentic Era
Yip, Jason
Gupta, Nikhil
Wojtyczka, Marcin
Paperback
Exercises and Projects for The Little SAS Book, Sixth Edition
Ottesen, Rebecca A.
Delwiche, Lora D.
Slaughter, Susan J.
Paperback