## ARIMA

ARIMA stands for autoregressive integrated moving average. It is a regression algorithm which is commonly used in univariate time series forecasting problems.

ARIMA stands for autoregressive integrated moving average. It is a regression algorithm which is commonly used in univariate time series forecasting problems.

The term multivariate generally refers to a property of a dataset having multiple variables being studied. In time series forecasting problems, multivariate refers to multiple variables being measured in given time series. The most common multivariate ML algorithm is VAR.

In machine learning, time series is a series of data, where values of certain features are presented in a sequence of time. There are univariate and multivariate time series in forecasting problems in machine learning. Univariate forecasting models make use of algorithms such as ARIMA and multivariate forecasting models make use of algorithms such as … Read more

In machine learning, univariate generally means that a property of a dataset has only a single variable which is being studied. Univariate is used in forecasting models, where only a single variable is being considered in a single time series. A common univariate ML algorithm is ARIMA.

VAR stands for vector autoregression. It is a regression algorithm commonly used in multivariate time series forecasting problems. See the ARIMA algorithm for univariate time series forecasting.