Applied Time Series Analysis
Preface
- Book package
- Authors
- Citation
- License
1 Basic matrix math in R
2 Linear regression in matrix form
3 Introduction to time series
4 Basic time series functions in R
5 Box-Jenkins method
6 Univariate state-space models
7 MARSS models
8 MARSS models with covariates
9 Dynamic linear models
10 Dynamic Factor Analysis
11 Covariates with Missing Values
12 JAGS for Bayesian time series analysis
13 Stan for Bayesian time series analysis
More examples
14 Detecting a signal from noisy sensors
15 Modeling changing seasonality
16 Modeling cyclic sockeye
References
Published with bookdown

Applied Time Series Analysis for Fisheries and Environmental Sciences

14.2 Prep

library(ggplot2)
library(MARSS)
library(stringr)
set.seed(1234)