Sentence examples for appropriate for forecasting the from inspiring English sources

Therefore, the model analyzed here is not appropriate for forecasting the effects of management decisions on one particular cod stock, but instead is meant to demonstrate expected trends and patterns for stocks and species with life histories similar to those investigated in this study.

Accordingly, in a recent comparison of the models' forecasting accuracy, the multivariate seasonal ARIMA model (SARIMA), an expanded form of ARIMA, was shown to be the most appropriate for forecasting the number of patients admitted to the emergency department per day, as it was built to incorporate explanatory variables affecting that number [ 20].

The results of the validation analyses show that the parsimonious model SARIMA (1,0,0)(1,0,1)12 was an appropriate model for forecasting the epidemics of BFV disease in Gladstone region because the RMS error was small (1.2; RMS percentage error = 0.73%).

The latter estimates are based on the recent 10-yr observed data, which may not be stationary and therefore may not be appropriate for forecasting.

We found that hybrid models (i.e., one model such as the Duong model for transient flow coupled with a different model, such as the Arps hyperbolic model with an appropriate value of the parameter "b") are appropriate for forecasting oil production and that it is possible to forecast solution gas production with availability of adequate data.

In addition, these models are suitable for forecasting stationary or trend time series, but they are not appropriate for forecasting seasonal time series.

According to the analysis results, a modeling data length of 70 is most appropriate for turbidity forecasting.

Key elements of economic forecasting include selecting the forecasting model(s) appropriate for the problem at hand, assessing and communicating the uncertainty associated with a forecast, and guarding against model instability.

The use of (t=5) min is reasonable and appropriate for near-field forecasting, e.g., in the Kanto region, because a real-time forecast is needed for evacuation purposes before the first arrival of a tsunami at the coast.

Then, I present some cases in which the null hypothesis of LBT is not appropriate for determining the merits of earthquake forecast models.

With appropriate forecasting formulas, the market for the product, and hence the total profit to expect at the old and new price, can then be projected.