Linear Models with R
β Scribed by Julian J Faraway
- Publisher
- Taylor & Francis
- Year
- 2014
- Tongue
- English
- Leaves
- 284
- Series
- Chapman & Hall/CRC Texts in Statistical Science
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Subjects
ΠΠΈΠ±Π»ΠΈΠΎΡΠ΅ΠΊΠ°;ΠΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½Π°Ρ Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΠ°;R;
π SIMILAR VOLUMES
Books on regression and the analysis of variance abound-many are introductory, many are theoretical. While most of them do serve a purpose, the fact remains that data analysis cannot be properly learned without actually doing it, and this means using a statistical software package. There are many of
"Like its widely praised, best-selling predecessor, this edition combines statistics and R to seamlessly give a coherent exposition of the practice of linear modeling. The text offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, fa
<p><P>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 po
Introduction: Basic notions about Bayesian inference -- Dynamic linear models -- Model classification -- Models with unknown parameters -- Sequential Monte Carlo methods.;State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics a