Time Series Analysis

Catalog description

Basic principles of time series methods and related statistical programming techniques, including seasonal-trend decomposition, autocorrelation functions, moving average, autoregression, autoregressive integrated moving average (ARIMA) models, Box-Jenkins methodology, prediction interval, generalized autoregressive conditionally heteroskedasticity (GARCH) models, and stochastic volatility models. Prerequisite: take STAT XXX (Any STAT course)