What are the different methods used in time series forecasting?

Time series forecasting is a popular technique for predicting the future using historical data. There are several methods used in time series forecasting, such as moving averages, exponential smoothing, ARIMA, and regression analysis. Moving averages involve calculating the average of the past few time periods to predict future values. Exponential smoothing is a method that assigns exponentially decreasing weights to past observations, giving more weight to recent values. ARIMA is a technique used for forecasting time series data by modeling the autocorrelation in the data, while regression analysis involves creating a model that uses one or more independent variables to predict the dependent variable. The choice of method depends on the nature of the data and the problem at hand.

This mind map was published on 7 June 2023 and has been viewed 103 times.