Hands-On Time Series Analysis
Introduction
1.
Everything Up-to-Date
2.
Quandl
2.1.
Access Quandl Databases
2.2.
Installation and Authentication
2.3.
Downloading Historical Data
2.3.1.
Using Additional Arguments of Quandl() Function
2.4.
Querying Quandl Databases from R Console
3.
Basic Visualization of Time Series
3.1.
plot()
3.2.
lines()
3.3.
legend()
4.
Random Walk and White Noise
4.1.
rnorm()
4.2.
set.seed()
4.3.
cumsum()
4.4.
Exercises
4.5.
Solutions
5.
Decomposing Time Series
5.1.
stl()
5.2.
Exercises
5.3.
Solutions
6.
ARMA Models
6.1.
fArma Package
6.2.
Exercises
6.3.
Solutions
7.
GARCH Models
7.1.
fGarch Package
7.2.
Exercises
7.3.
Solutions
8.
Advanced Time Series Visualization
8.1.
Static Graphics
8.1.1.
quantmod Package
8.1.2.
ggplot2 Package
8.2.
Interactive Graphics
8.2.1.
plotly Package
8.2.2.
shiny and rcharts Packages
Powered by
GitBook
A
A
Serif
Sans
White
Sepia
Night
Share on Twitter
Share on Google
Share on Facebook
Share on Weibo
Share on Instapaper
Hands-On Time Series Analysis
ARMA Models
Analysis of ARMA models in
R
can be done with the
fArma
package.