# Multivariate vs Multiple time series

While looking through the concepts of multivariate time series I came across the term "Multiple" time series.

Is both the terms are pointing to the same meaning. What is the difference between them in time series analysis

Multiple time series is just that: Multiple series instead of a single series.

Multivariate time series is usually contrasted with univariate time series, where each observation at a time $t$ is a vector of values instead of a single value. Typically for such series, the variables in the vector are closely interrelated, which is why we consider them to be single observation in vector form instead of distinct observations from separate time series.

To better explain the difference consider the following examples:

• We want to monitor weight for a group of patients: This would be multiple time series, i.e. the daily weight values for each patient is a separate time series.

• We want to monitor the health of a single patient, so we keep track of the patient's daily weight, daily body temperature, daily blood pressure, daily cholesterol levels, etc...: This would be a multivariate time series.

Multivariate regression models: Pertaining to multiple dependent variables.

Multiple regression models: Pertaining to multiple independent variables.

Time series: Pertaining to repeated measurements of the same variables over time (typically with many repetitions).

These can be combined, for example multiple multivariate regression models of time series data.