Sentence examples for mean absolute prediction from inspiring English sources

To determine the best model among the entire dataset, predictive ability was evaluated using root mean square error (RMSE), mean absolute prediction error (MAPE), and predictive ratios of predicted to observed cost (PR) among deciles of predicted cost, by comparing point estimates and 95% bias-corrected bootstrap confidence intervals.

Two questions of interest arise: 1) Which statistical model works best for our sample of over 500,000 patients if the criteria for the prediction model are low root mean square error (RMSE), low mean absolute prediction error (MAPE), and predictive ratio (PR) around 1 for the entire range of patient costs?

The final model had good aggregate and individual level predictive accuracy, with the mean absolute prediction error estimated at 20% of the mean cost (see Additional file 1: Table S5).

The predictive performance of each model was evaluated using the model prediction error (PE), mean prediction error (MPE), mean absolute prediction error (MAPE), prediction-corrected visual predictive check (pcVPC), and normalized prediction distribution errors (NPDE).

The first was the mean prediction error (MPE), which measures the bias and predictive accuracy, and the second was the mean absolute prediction error (MAPE): MPE=frac{1}{n}{displaystyle sum_{i=1}^nleft {y}_i-{widehat{y}}_iright)} MAPE=frac{1}{n}{displaystyle sum_{i=1}^nleft|{y}_i-{widehat{y}}_ikern0.1em right|}.

Ultrasonic algorithms had mean absolute prediction errors that ranged from ±263 to 646 g (±7.5%−18.8%).

The performance of each alternative model was compared by its predictive R-square and mean of absolute prediction error (MAPE) estimated by the validation sample.

The best single point marker was Ctrough (discordance, 12.1 %; mean absolute percentage prediction error, 11.42 %; R = 0.78).

The best two point markers were Ctrough and C3 (discordance, 3.0 %; mean absolute percentage prediction error, 5.2 %; R = 0.88).

The best three point markers were Ctrough, C2, and C3 (a discordance of 1.52 % and a mean absolute percentage prediction error of 7.61 %, and R = 0.97).

The limited sampling formula of Ctrough (22.213*Ctrough + 47.983) for once-daily tacrolimus in predicting systemic exposure had a moderate correlation with full trapezoidal AUC24 (a discordance of 18.2 %, a mean absolute percentage prediction error of 13.3 %, and R = 0.72).