Sentence examples for approximation of the prediction from inspiring English sources

Using linear regression, we obtain the following approximation of the prediction error, Figure 2 Error distribution as a function of delay and speed in the prediction.

In addition, emBayesR uses an approximation of the prediction error variance of all other SNPs when estimating g i. Bayesian estimates are sensitive to the prior if the data does not contain enough information to overwhelm the prior.

In addition, a first-order approximation of the predictions of the model is used to obtain the waveforms of the vibration, and the peak of the amplitude frequency curve reveals the occurrence of resonance.

Alternatively Monte Carlo sampling can be used to calculate approximations of the prediction error variance, which converge to the true values if enough samples are used.

This work aims to estimate the limitations of the van der Waals one-fluid (vdW1) approximation in the prediction of the viscosity of Lennard Jones (LJ) mixtures.

A new theoretical approximation for expectation of the prediction error is derived using the same-realization predictions.

The design criteria are evaluated using prediction methods and fitness approximations of these prediction methods.

The close comparison between the observed and simulated contaminant concentration in the aqueous phase showed that the approximation of the pulsed sparging operation yielded reasonable prediction of the removal process.

In RNMF, we extend the NMF objective function by adding a label matrix factorization term and an additional network regularization term to encode the network structure and label information of proteins, and we seek a matrix factorization which gives a new data representation that provides a good approximation of the original data matrix to make prediction for the unlabeled proteins.

Then, N particles are drawn from the Gaussian approximation of prediction: {boldsymbol{X}^{n}_{k} sim mathcal{N}(boldsymbol{x}_{k};~boldsymbol{bar{x}}_{k|k-1},~boldsymbol{P}_{k|k-1})}^{N}_{n=1}.

The prediction stage produces an approximation of the a priori p.d.f begin{aligned} P(x_k) = frac{1}{N} sum ^N_{i=0}delta _{x^i_k} (x_k), end{aligned} (6 where (delta _x) denotes Dirac's measure and N is the number of particles.