The Yamartino method is a well-known approach used for estimating the parameters of statistical models, particularly in the field of time series analysis. It focuses on time series data where the observations are influenced by seasonality or periodic effects. The method involves decomposing the time series into its components—trend, seasonality, and error. One of the main applications of the Yamartino method is in forecasting, where it helps in providing more accurate predictions by taking into account the seasonal structure of the data.
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