Dynamic Linear Models with R (English, Giovanni Petris | Sonia Petrone | Patrizia Campagnoli)

must have for state space/dynamic linear modeling

I did use this book for the last 4 years.I believe that the quality of this book must be appreciated in context. As one reviewer stated (and I fully support that) - this is a very good description of how to apply the dlm package with well-selected examples. Its strengths are: (1) very well written package - I did learn some new things about R while analyzing the code; (2) good examples illustrating finer points of dynamic modeling in multiple contexts; (3) clear though sometimes terse explanati

Five Stars

Good book. Excellent service.

Useful book so far; Kindle edition has OCR issues

The book has been useful so far; I'm only partway in so I can't comment on everything, but so far it's a good overview of the math behind many of the more complicated modeling and predictive techniques being used today.Unfortunately the Kindle edition suffers from occasional but significant OCR issues in the math in the running text, and for a mathematical book that's a killer -- *all* the formatting needs to be preserved *all* the time, or the equations and their explanation don't make sense.

Clear and to the point

This book might be seen as extended documentation for the R package dlm, authored by Petris. It is in fact more than that. It discusses clearly the theory foundations from a Bayesian point of view, even if the length of the book implies that the discussion has to be terse at times. R code and examples are interspersed with the theory, greatly enhancing reader understanding.This is a good buy for any applied statistician learning or using state-space models.Although it stands on its own, I think

Good implementation of Bayesian DLMs in R

The only problem is that the book website no longer seems available, making some example data and other items (some R scripts by the authors) hard to find.