This repo contains an adaptation of the notes on Time Series Analysis from Penn State, located at https://onlinecourses.science.psu.edu/stat510/. The original course is given in R, but these notes use Python, Pandas, and Statsmodels in Jupyter Notebooks. Hopefully these notes are useful and educational.
- Understanding the characteristics of time series data
- Understanding moving average models and partial autocorrelation as foundations for analysis of time series data
- Exploratory Data Analysis - Trends in time series data
- Using smoothing and removing trends when working with time series data
- Understanding how periodograms are used with time series data
- Implementing ARMA and ARIMA time series models
- Identifying and interpreting various patterns for intervention effects
- Examining the analysis of repeated measures design
- Using ARCH and AR models in multivariate time series contexts
- Using spectral density estimation and spectral analysis
- Using fractional differencing and threshold models with time series data
"Time Series Analysis and Its Applications With R Examples", 3rd edition by Robert H. Shumway & David S. Stoffer