Sentence examples for model estimation and from inspiring English sources

Model Estimation and Selection: We estimated the posterior distributions of the hierarchical Bayesian models using Markov chain Monte Carlo (MCMC) methods.

Further, our Bayesian approach allowed us to obtain not only point estimates of the modes' locations, but the whole posterior distribution that informed us also on the uncertainty on the estimated modes' locations (for full details on model, estimation and results we refer to LFH, NB, and HKvD, manuscript in preparation).

Taken together, these results suggest that, although parameter and branch length estimation error were correlated in simple simulations, this correlation may have reflected a single underlying cause (such as insufficient data to estimate either parameter) rather than a causative relationship between model estimation and branch length estimation.

Model estimation and data simulation were performed using NONMEM version 5.1.

It also features a neighborhood selection scheme based on smoothed context maps, for both model estimation and neighbor combination.

The processes of model estimation and prediction by kriging in three dimensions are similar to those in two dimensions.

Three patterns of estimates were made: estimates made from logarithmic approximations of all items (logarithm-model estimation), estimates made from linear approximations of all items (linear-model estimation), and estimates made from approximations of items with higher determination coefficients (mixed-model estimation).

The RMS errors between model estimations and experimental data in the literature were about 0.1 log unit.

Excessive number of harmonic oscillator will generate inaccurate model estimations and predictions.

Figures 1, 2, 3, 4, 5, 6, 7 show both lognormal model estimations and Kaplan-Meier curves for the different periods.

Section 4.2 presents the proposed adaptive motion smoothing using multiple-model estimation and how to modify it with estimate projection.