Sentence examples for fitting data for from inspiring English sources

The mean square error of prediction for each of the methods and fitting data for both cell types indicate that increasing the number of points reduces the mean square error.

The results obtained from kinetic analysis and fitting data for both the forward and backwards processes show that nucleophilic addition into benzaldehydes bearing a 2-heteroatom substisuent is particularly fast.

The less than two-fold difference for the range of values obtained from fitting data for individual resonances suggests that the residues that exhibit exchange could be involved in the same dynamic phenomenon.

These include varying the amount of fitting data for the forecasting methods, smoothing of the fitting data, different methods for interpolating gaps in the data, the longshore aggregation of data, making forecasts for coastal profiles with and without nourishments, and making forecasts up to five years ahead.

> -wrap-foot>Table  2 shows the 4P model fitting data for curves in sample extracts.

The curve fitting data for this characterization are included in Additional file 3. A comparison of the intensity ratios I1650/ I1440 and I3003/ I1440, is found to be satisfactory as both intensity ratios, I1650/ I1440 and I3003/ I1440, corresponding to CC-503 (row 3) are close to the values obtained for the same fatty acid standard (oleic acid, row 2).

The fitted models were evaluated for fit on the fitting data set and for prediction performance on the split-validation and independent-validation data sets.

While the relative performance of the hierarchical model is influenced by biases within the fitting data, particularly for woodland and conifer species, our results suggest that poor representation of individual tree model error may lead to unrealistically high confidence in plot-scale estimates of biomass stocks derived from forest inventory data.

Here we develop statistical and computational methods for fitting fitness data from mutation combinatorial networks to three simple models: additive, multiplicative and stickbreaking.

This study investigates 4 different methods for fitting data and estimating the parameters of the Weibull distribution namely, good linear unbiased estimators, least squares regression, weighted least squares regression and maximum likelihood estimation.

Evaluated structures used different parameter number for fitting data.