ARMA and ARIMA: Preliminaries and Setup AR and MA Models ARMA and ARIMA models are best understood as combinations of their two core components: autoregressive (AR) and moving-average (MA) models....

Ethereum Time Series EDA Pt. 3 In-sample vs. out-of-sample forecasting In time series, in-sample and out-of-sample forecasts are most easily explained in terms of train and validation/test sets. Th...

Ethereum Time Series EDA Pt. 2 (For context, please consider reading Part 1 of this analysis) A stochastic process is defined as a sequence of random variables understood to have happened over a c...

Ethereum Time Series EDA Pt. 1 The goal of this post (and subsequent posts) is to walk through an exploratory data analysis (EDA) I did for a time series analysis and forecasting project on the cry...