An autoregressive integrated moving average (ARIMA) model is a statistical analysis model that leverages time series data to forecast future trends.

One example is the Autoregressive Integrated Moving Average (ARIMA), a sophisticated autoregressive model that factors in trends, cycles, seasonality, errors, and other non-static data when making ...

Methods: In this time series forecast, autoregressive integrated moving average models (ARIMA) were constructed based on 2004-2016 historic breast cancer incidence rates, as reported by the NCDB.

ARIMA is an acronym for AutoRegressive Integrated Moving-Average. The order of an ARIMA model is usually denoted by the notation ARIMA(p,d,q), where Thus, when an autoregressive operator and a mean ...

Moving-average errors can be difficult to estimate. You should consider using an AR(p) approximation to the moving average process. A moving average process can usually be well-approximated by an ...

In a new study, researchers used seasonal autoregressive integrated moving averages to estimate excess mortality, defined as the difference between the number of observed and expected deaths, in ...