Dynamic Time Series Models Using R Inla
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Dynamic Time Series Models Using R Inla
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Author : Nalini Ravishanker
language : en
Publisher: CRC Press
Release Date : 2022-08-10
Dynamic Time Series Models Using R Inla written by Nalini Ravishanker and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-10 with Mathematics categories.
Dynamic Time Series Models using R-INLA: An Applied Perspective is the outcome of a joint effort to systematically describe the use of R-INLA for analysing time series and showcasing the code and description by several examples. This book introduces the underpinnings of R-INLA and the tools needed for modelling different types of time series using an approximate Bayesian framework. The book is an ideal reference for statisticians and scientists who work with time series data. It provides an excellent resource for teaching a course on Bayesian analysis using state space models for time series. Key Features: Introduction and overview of R-INLA for time series analysis. Gaussian and non-Gaussian state space models for time series. State space models for time series with exogenous predictors. Hierarchical models for a potentially large set of time series. Dynamic modelling of stochastic volatility and spatio-temporal dependence.
Ordered Data Analysis Modeling And Health Research Methods
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Author : Pankaj Choudhary
language : en
Publisher: Springer
Release Date : 2015-12-14
Ordered Data Analysis Modeling And Health Research Methods written by Pankaj Choudhary and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-14 with Mathematics categories.
This volume presents an eclectic mix of original research articles in areas covering the analysis of ordered data, stochastic modeling and biostatistics. These areas were featured in a conference held at the University of Texas at Dallas from March 7 to 9, 2014 in honor of Professor H. N. Nagaraja’s 60th birthday and his distinguished contributions to statistics. The articles were written by leading experts who were invited to contribute to the volume from among the conference participants. The volume is intended for all researchers with an interest in order statistics, distribution theory, analysis of censored data, stochastic modeling, time series analysis, and statistical methods for the health sciences, including statistical genetics.
Applied Bayesian Modelling
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Author : Peter Congdon
language : en
Publisher: John Wiley & Sons
Release Date : 2014-06-25
Applied Bayesian Modelling written by Peter Congdon and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-25 with Mathematics categories.
This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBUGS and OPENBUGS. This feature continues in the new edition along with examples using R to broaden appeal and for completeness of coverage.
Handbook Of Discrete Valued Time Series
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Author : Richard A. Davis
language : en
Publisher: CRC Press
Release Date : 2016-01-06
Handbook Of Discrete Valued Time Series written by Richard A. Davis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-06 with Mathematics categories.
Model a Wide Range of Count Time Series Handbook of Discrete-Valued Time Series presents state-of-the-art methods for modeling time series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the book focuses on time series of counts, some of the techniques discussed ca
Spatio Temporal Methods In Environmental Epidemiology With R
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Author : Gavin Shaddick
language : en
Publisher: CRC Press
Release Date : 2023-12-12
Spatio Temporal Methods In Environmental Epidemiology With R written by Gavin Shaddick and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-12 with Medical categories.
Spatio-Temporal Methods in Environmental Epidemiology with R, like its First Edition, explores the interface between environmental epidemiology and spatio-temporal modeling. It links recent developments in spatio-temporal theory with epidemiological applications. Drawing on real-life problems, it shows how recent advances in methodology can assess the health risks associated with environmental hazards. The book's clear guidelines enable the implementation of the methodology and estimation of risks in practice. New additions to the Second Edition include: a thorough exploration of the underlying concepts behind knowledge discovery through data; a new chapter on extracting information from data using R and the tidyverse; additional material on methods for Bayesian computation, including the use of NIMBLE and Stan; new methods for performing spatio-temporal analysis and an updated chapter containing further topics. Throughout the book there are new examples, and the presentation of R code for examples has been extended. Along with these additions, the book now has a GitHub site (https://spacetime-environ.github.io/stepi2) that contains data, code and further worked examples. Features: • Explores the interface between environmental epidemiology and spatio-temporal modeling • Incorporates examples that show how spatio-temporal methodology can inform societal concerns about the effects of environmental hazards on health • Uses a Bayesian foundation on which to build an integrated approach to spatio-temporal modeling and environmental epidemiology • Discusses data analysis and topics such as data visualization, mapping, wrangling and analysis • Shows how to design networks for monitoring hazardous environmental processes and the ill effects of preferential sampling • Through the listing and application of code, shows the power of R, tidyverse, NIMBLE and Stan and other modern tools in performing complex data analysis and modeling Representing a continuing important direction in environmental epidemiology, this book – in full color throughout – underscores the increasing need to consider dependencies in both space and time when modeling epidemiological data. Readers will learn how to identify and model patterns in spatio-temporal data and how to exploit dependencies over space and time to reduce bias and inefficiency when estimating risks to health.
Bayesian Hierarchical Models
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Author : Peter D. Congdon
language : en
Publisher: CRC Press
Release Date : 2019-09-16
Bayesian Hierarchical Models written by Peter D. Congdon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-16 with Mathematics categories.
An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods. The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples. The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities. Features: Provides a comprehensive and accessible overview of applied Bayesian hierarchical modelling Includes many real data examples to illustrate different modelling topics R code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementation Software options and coding principles are introduced in new chapter on computing Programs and data sets available on the book’s website
Green Materials And Technology
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Author : Subaer,
language : en
Publisher: Trans Tech Publications Ltd
Release Date : 2019-08-16
Green Materials And Technology written by Subaer, and has been published by Trans Tech Publications Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-16 with Technology & Engineering categories.
International Symposium on Green Materials and Technology (ISGMT) Selected, peer reviewed papers from the 1st International Symposium on Green Materials and Technology (1st ISGMT), September 29 – 30, 2018, Makassar, Indonesia
Dynamic Linear Models With R
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Author : Giovanni Petris
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-12
Dynamic Linear Models With R written by Giovanni Petris and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-12 with Mathematics categories.
State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.
Change Point Detection And Spatio Temporal Analysis Of Discontinuous Sawtooth Time Series Of Regressions Using R Inla
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Author : Marie-Agnès S. Tellier
language : en
Publisher:
Release Date : 2018
Change Point Detection And Spatio Temporal Analysis Of Discontinuous Sawtooth Time Series Of Regressions Using R Inla written by Marie-Agnès S. Tellier and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Aquatic sciences categories.
Time series analysis was developed to address the correlation between consecutive observations that traditional regression ignores. However, what to do when one encounters data that are time series of regressions, a repetition of time series creating a motif? Whether by hunting or fishing, any removal of animals of limited population from their environment is usually regulated by the government in order to preserve stock and future availability, and prevent species extinction. As such, most regulated species undergo a sequence of closed-open sporting seasons creating a pattern of repeated regressions with structural discontinuity. In the presence of such structural discontinuity, could one find and estimate change points, or drastic change in the mean response, in the time series. Moreover, most data collected in ecology often have spatial information attached to them. Thus, in addition to the temporal correlation, one should also model the spatial correlation present in the data. This dissertation introduces the use of R-INLA in (1) estimating model parameters for discontinuous, dynamic, two-scale Bayesian regression models rather than the more traditional but extremely time consuming approach of using MCMC, (2) establishing an adequate method in finding and estimating change points in the mean in such models, and (3) easily extending such Bayesian dynamic model to Spatio-temporal settings. Real life applications and results are showed using spiny lobster (Panulirus argus) commercial trap fishery data collected daily by the State of Florida between 1995 and 2015.
The Analysis Of Time Series
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Author : Chris Chatfield
language : en
Publisher: CRC Press
Release Date : 2019-04-25
The Analysis Of Time Series written by Chris Chatfield and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-25 with Mathematics categories.
This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models.