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.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
