Sentence examples for error observations from inspiring English sources

Furthermore, near-optimal diagnostic accuracy (exonerating over 80% of the blocks of code on average) is already obtained for low-quality error observations and limited numbers of test cases.

The field of Bioscience has a storied history built on early trial and error observations of the natural world and scientific discoveries that have now provided us with a means for taking the planetary pulse of life-support systems and making adjustments to human consumption and population levels, drivers of ecosystem degradation.

Using the aforementioned datasets, the performance of the hydrological model in estimating ETa was improved using both calibration techniques by achieving Nash-Sutcliffe efficiency (NSE) values >0.5 (0.73–0.85), percent bias (PBIAS) values within ±25% (±21.73%), and root mean squared error – observations standard deviation ratio (RSR) values <0.7 (0.39–0.52).

First, these measurements need to be transformed into error observations.

PMRs themselves reported reliance on package instructions, their own experience gained from trial and error, observations of treatments used in clinics and mass media advertising for information on use of medicines.

Accuracy was calculated according to Bragdon et al. (2002), using the modified equation: where x was obtained from the Student's t-test distribution (x = 2.228), s is the standard deviation of the sample, n is the number of examinations, and m is the number of error observations per examination.

Although the yaw error observation period is very short, it is sufficiently accurate for a carriage yaw sensor.

The results are favorable to TE programs on several parameters: the incidence of error observation to treatment appears to be less important in (for) patients following a TE program.

This paper develops a new approach for evaluating multi-step system forecasts with relatively few forecast-error observations.

(2014) to generate "design-free" estimates of the general matrix of the forecast-error second-moment when there are relatively few forecast-error observations.

Multi-objective function statistics: P-factor (23%, 12%), R-factor (0.63, 0.40), Nash Sutcliffe efficiency, NSE (0.55, 0.53), root mean square error-observations standard deviation ratio (RSR) (0.67, 0.69), coefficient of determination, R2 (0.52, 0.52), and percent bias, PBIAS (− 14.6%, 0.8%) for calibration and validation, respectively were obtained.