 Regression with time series structure

Regression with time series structure refers to the application of regression analysis techniques to data that is ordered in time. Time series data is characterized by observations collected sequentially over time, and it often has properties such as trends, seasonality, autocorrelation, and non-stationarity. Here’s an overview of key aspects of regression with time series: ### 1.