Sentence examples for forecast bias from inspiring English sources

The magnitudes of the forecast bias and state error covariances are calibrated by optimizing the innovation statistics of groundwater storage.

To date, an outstanding issue in hydrologic data assimilation is a proper way of dealing with forecast bias.

A referencing of greater pricing activity for the industry and increased second half investment needs for the group suggests neutral forecast bias at best.

Comparison of the track forecast bias between deterministic forecasts and TCB ensemble forecasts shows however that both the TCB ensemble and the deterministic forecasts possess similar pattern of the cross- and along-track forecast errors.

Overall, the results in this paper justify the use of the traditional approach for online bias estimation with a persistent bias model and a simplified forecast bias error covariance estimation.

Persistent bias models are most often used to propagate the bias estimate, where the a priori forecast bias error covariance is calculated as a constant fraction of the unbiased a priori state error covariance.

In a local-asymptotic parameterization of the probability of breaks, we provide analytical expressions for forecast biases and mean-square forecast errors.

However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product.

But when King, Kashin, and Soneji collected every policy score from the past several decades and compared them to the forecasting bias, the result was troubling.

Understanding human behavior is crucial for investors, according to Alliance Capital Management CEO Lewis Sanders, who talked about behavioral finance and its role in pricing anomalies and forecasting bias during a presentation at Wharton.

However, this evidence is insufficient to determine whether timber market models that rely on conventional timber supply specifications will suffer from significant forecasting biases.