Measures of forecast accuracy are important factors in comparing different forecasting methods and finding good _________________.

Measures of forecast accuracy are crucial because they allow for the assessment of how well a specific forecasting method performs in predicting future events or outcomes. When trying to find good parameters, one needs to ensure that these parameters lead to forecasts that are as accurate as possible. Parameters such as coefficients in regression models or weights in time series analysis are essential for understanding the relationship within the data and improving the predictive performance of the model.

In the context of comparisons among different forecasting approaches, understanding the accuracy measures enables practitioners to refine these parameters, possibly leading to more effective forecasting.

The terminology used in the other choices, while relevant in different contexts, does not directly tie to the immediate need for accuracy evaluation in forecasting. For instance, while models are built using parameters, the focus in this question is on the evaluation of those parameters to optimize forecasting methods, thus highlighting the importance of parameters specifically in achieving accurate forecasts.