The autoregressive moving average is an example of a causal/econometric method for the forecasting project performance. The casual/econometric forecasting method uses the assumption that it is possible to identify the underlying factors, which might influence the variable being forecasted. For example, sales of umbrellas might be associated with weather conditions. If the causes are understood, projections of the influencing variables can be made and used in the forecast. Some examples of casual/econometric forecasting method are as follows: Regression analysis using linear regression or non-linear regression Autoregressive moving average (ARMA) Autoregressive integrated moving average (ARIMA) Econometrics
Answer option B is incorrect. The time series method relies on the earned value, moving average, extrapolation, and growth curve.
Answer option A is incorrect. The judgmental methods use intuition, the Delphi method, and forecast by analogy.
Answer option C is incorrect. The ensemble forecasting is not part of the causal/econometric method for forecasting.
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