Time Series with Multiple Attributes for Each Year

1. What is a multivariate time series?
2. Which time series forecasting model involves the linear combination of past time series values of the target variable to predict future values?

What is a multivariate time series?

A Multivariate Time Series consist of more than one time-dependent variable and each variable depends not only on its past values but also has some dependency on other variables.

Which time series forecasting model involves the linear combination of past time series values of the target variable to predict future values?

AutoRegressive Integrated Moving Average (ARIMA) models are among the most widely used time series forecasting techniques: In an Autoregressive model, the forecasts correspond to a linear combination of past values of the variable.