ATSA21 Lecture 2: Stationarity & introductory functions

ATSA 2021

Lecture 1: Intro to time series analysis
Lecture 2: Stationarity & introductory functions
Lecture 3: Intro to ARMA models
Lecture 4: Fitting and Selecting ARIMA models
Lecture 5: More Fitting ARIMA models
Lecture 6: Univariate State-Space Models
Lecture 7: Multivariate State-Space models
Lecture 8: ARMA and MARSS models with covariates
Lecture 9: Dynamic factor analysis (DFA)
Lecture 10: Dynamic linear models (DLMs)
Lecture 11: Hidden Markov models
Lecture 12: Univariate Bayesian estimation
Lecture 13: Multivariate Bayesian estimation
Lecture 14: Multi-model inference and selection
Lecture 15: B Matrix Estimation
Lecture 16: Semi- and non-parametric models
Lecture 17: Frequency domain models
Lecture 18: Spatio-temporal models 1
Lecture 19: Spatio-temporal models 2
Lecture 20: Regression versus State Space