Statistical Methods for Spatio-Temporal Systems, Finkenstadt, Barbel
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Gelfand, Alan E. Fuentes, Montserrat Guttorp, Pete Название: Handbook of spatial statistics ISBN: 1420072870 ISBN-13(EAN): 9781420072877 Издательство: Taylor&Francis Рейтинг: Цена: 103610.00 T Наличие на складе: Есть Описание: Offers an introduction detailing the evolution of the field of spatial statistics. This title focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and, spatial point patterns.
Название: Statistical methods for spatio-temporal systems ISBN: 0367390116 ISBN-13(EAN): 9780367390112 Издательство: Taylor&Francis Рейтинг: Цена: 65320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities.
Contributed by leading researchers in the field, each self-contained chapter starts with an introduction of the topic and progresses to recent research results. Presenting specific examples of epidemic data of bovine tuberculosis, gastroenteric disease, and the U.K. foot-and-mouth outbreak, the first chapter uses stochastic models, such as point process models, to provide the probabilistic backbone that facilitates statistical inference from data. The next chapter discusses the critical issue of modeling random growth objects in diverse biological systems, such as bacteria colonies, tumors, and plant populations. The subsequent chapter examines data transformation tools using examples from ecology and air quality data, followed by a chapter on space-time covariance functions. The contributors then describe stochastic and statistical models that are used to generate simulated rainfall sequences for hydrological use, such as flood risk assessment. The final chapter explores Gaussian Markov random field specifications and Bayesian computational inference via Gibbs sampling and Markov chain Monte Carlo, illustrating the methods with a variety of data examples, such as temperature surfaces, dioxin concentrations, ozone concentrations, and a well-established deterministic dynamical weather model.
Автор: Shaddick, Gavin Название: Spatio-Temporal Methods in Environmental Epidemiology ISBN: 0367783460 ISBN-13(EAN): 9780367783464 Издательство: Taylor&Francis Рейтинг: Цена: 43890.00 T Наличие на складе: Поставка под заказ.
Автор: Andrew Zammit-Mangion; Michael Dewar; Visakan Kadi Название: Modeling Conflict Dynamics with Spatio-temporal Data ISBN: 3319010379 ISBN-13(EAN): 9783319010373 Издательство: Springer Рейтинг: Цена: 47880.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book also demonstrates the methods on the WikiLeaks Afghan War Diary, the results showing that this approach allows deeper insights into conflict dynamics and allows a strikingly statistically accurate forward prediction of armed opposition group activity in 2010, based solely on data from preceding years.
Автор: Lawson, Andrew B. Название: Using r for bayesian spatial and spatio-temporal health modeling ISBN: 0367490129 ISBN-13(EAN): 9780367490126 Издательство: Taylor&Francis Рейтинг: Цена: 117390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested in applying Bayesian methodology in small area health data studies.
Автор: Sahu Sujit Название: Bayesian Modeling of Spatio-Temporal Data with R ISBN: 0367277980 ISBN-13(EAN): 9780367277987 Издательство: Taylor&Francis Рейтинг: Цена: 100030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is designed to make spatio-temporal modeling and analysis understandable to students and researchers, mathematicians and statisticians and practitioners in the applied sciences. By avoiding hardcore math and calculus, this book aims to be a bridge that removes the statistical knowledge gap from among the applied scientists.
Автор: Lawson, Andrew B. Название: Using R for Bayesian Spatial and Spatio-Temporal Health Modeling ISBN: 0367760673 ISBN-13(EAN): 9780367760670 Издательство: Taylor&Francis Рейтинг: Цена: 46950.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Christopher H Schmid Название: Handbook Of Meta-Analysis ISBN: 1498703984 ISBN-13(EAN): 9781498703987 Издательство: Taylor&Francis Рейтинг: Цена: 163330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Meta-analysis is the application of statistics to combine results from multiple studies and draw appropriate inferences. Its use and importance have exploded over the years as the need for a robust evidence base has become clear in many scientific areas like medicine and health, social sciences, education, psychology, ecology and economics.
Автор: Norou Diawara Название: Modern Statistical Methods for Spatial and Multivariate Data ISBN: 3030114309 ISBN-13(EAN): 9783030114305 Издательство: Springer Рейтинг: Цена: 79190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques.
Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
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