Time Series
About
I Example
1
Example of Time Series Data
1.1
Characteristics of Time Series
1.1.1
Practical data
1.1.2
White Noise (WN)
1.1.3
Random Walk
1.1.4
Noise influence periodic
1.1.5
How lag influence plot
1.2
Explore Data
1.2.1
Estimate a linear trend
1.2.2
Detrend and Differencing
1.2.3
Smoothing
1.3
Time Series model
1.3.1
Behavior of the ACF and PACF for ARMA models
1.4
Fit model with different method
1.4.1
Preliminary Analysis
1.4.2
Fit AR(2) model to Recruitment Series
1.4.3
compare AR(2) model’s coef. estimated by OLS, YW, and MLE
1.5
Analysis of GNP Data
1.5.1
Diagnostics
1.5.2
model selection
1.6
Model Diagnostics
1.7
Regression with Autocorrelated Errors
1.8
Multiplicative Seasonal ARIMA Models
1.9
Periodogram
II Introduction
2
About Time Series
2.1
What is time series?
2.2
Plot of time series data
2.3
Why use time series
2.4
Objective of time series analysis
2.5
Modeling strategy
III Definition
3
Base Definition
3.1
Variance, Covariance, Correlation
3.2
Uncorrelated, Independent
3.3
Autocovariance, Autocorrelation, Cross-covariance, Cross-correlation
3.3.1
Population
3.3.2
Stationary Case
3.3.3
Sample
4
Modeling dependence
4.1
Stationary
4.2
Weakly Stationary
4.3
White Noise (WN)
4.4
Random Walk Process
by ZIH-YING, LI
Time Series
Time Series
ZIH-YING, LI
About
Personal note for
Time Series
Course
Reference Book
Robert H. Shumway, David S. Stoffer
, Time series analysis and its application with R examples. 4
th
edition.
Using package in R
astsa
package