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Bayesian Regression Modeling with INLA, Wang, Xiaofeng
Автор: Gomez-rubio, Virgilio Название: Bayesian inference with inla ISBN: 1032174536 ISBN-13(EAN): 9781032174532 Издательство: Taylor&Francis Рейтинг: Цена: 6889.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Integrated Nested Laplace Approximation (INLA) is a popular method for approximate Bayesian inference. This book provides an introduction to the underlying INLA methodology and practical guidance on how to fit different models with R-INLA and R. This covers a wide range of applications, such as multilevel models, spatial models and survival
Описание: The Integrated Nested Laplace Approximation is a popular method for approximate Bayesian inference. INLA is an alternative to other methods for Bayesian inference, such as Markov Chain Monte Carlo, that are more computationally demanding. In addition, the R-INLA package for the R statistical software provides a way to fit such models in practice
Автор: Moraga, Paula Название: Geospatial health data ISBN: 036735795X ISBN-13(EAN): 9780367357955 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book shows how to model disease risk and quantify risk factors using areal and geostatistical data. It also shows how to create interactive maps of disease risk and risk factors, and describes how to build interactive dashboards and Shiny web applications that facilitate the communication of insights to collaborators and policy makers.
Автор: Ravishanker, Nalini (university Of Connecticut, Storrs, Usa) Raman, Balaji (cogitaas Ava, Mumbai, India) Soyer, Refik Название: Dynamic time series models using r-inla ISBN: 036765427X ISBN-13(EAN): 9780367654276 Издательство: Taylor&Francis Рейтинг: Цена: 12707.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This Book 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.
Автор: Thrane, Christer (inland Norway University Of Applied Sciences, Norway) Название: Doing statistical analysis ISBN: 1032171324 ISBN-13(EAN): 9781032171326 Издательство: Taylor&Francis Рейтинг: Цена: 7501.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Doing Statistical Analysis looks at three kinds of statistical research questions - descriptive, associational and inferential - and shows students how to conduct statistical analyses and interpret the results.
Автор: Darwiche Название: Modeling and Reasoning with Bayesian Networks ISBN: 1107678420 ISBN-13(EAN): 9781107678422 Издательство: Cambridge Academ Рейтинг: Цена: 9821.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis.
Автор: Bradley A. Hartlaub Название: STAT2: Modeling with Regression and ANOVA ISBN: 1319054072 ISBN-13(EAN): 9781319054076 Издательство: Macmillan Learning Рейтинг: Цена: 16432.00 р. Наличие на складе: Нет в наличии.
Описание: The book will appeal to a diverse audience, including advocates and sceptics, academics and practitioners, transitional justice specialists and readers from other sectors (development, peace-building and human rights), and to a genuinely multi-disciplinary cohort of scholars. Its value lies in its contribution to both conceptual and practice-based thinking on transformative justice.
Описание: It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data.
Автор: Mcnulty, Keith Название: Handbook of regression modeling in people analytics ISBN: 1032041749 ISBN-13(EAN): 9781032041742 Издательство: Taylor&Francis Рейтинг: Цена: 10258.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling.
Автор: David G. T. Denison Название: Bayesian Methods for Nonlinear Classification and Regression ISBN: 0471490369 ISBN-13(EAN): 9780471490364 Издательство: Wiley Рейтинг: Цена: 20584.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Regression analysis models the relationship between a set of responses and another variable: for example, to estimate the true position of a line through a number of observed points. Unfortunately, data rarely conforms to simple curves and straight lines - parametric models - and this text examines more complex - or nonparametric - models.
Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data.
New to the Second Edition
Reorganized to focus on unbalanced data
Reworked balanced analyses using methods for unbalanced data
Introductions to nonparametric and lasso regression
Introductions to general additive and generalized additive models
Examination of homologous factors
Unbalanced split plot analyses
Extensions to generalized linear models
R, Minitab(R), and SAS code on the author's website
The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.
Описание: It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data.
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