Sentence examples for more efficient estimations from inspiring English sources

Although there are many different alternatives, MCMC-based particle filters have been shown to obtain the more efficient estimations of the posterior for high-dimensional problems [13] using the Metropolis-Hastings sampling algorithm.

Based on these observations, we hypothesize that the objective function manifold that uses a combination of RMSE and constraints gets rid of various local minima that correspond to physically meaningless parameter estimates and thus facilitates a much more efficient estimation of parameter values.

Arellano and Bond (1991) then proposed a more efficient estimation procedure.

The future work in this area may build upon them to develop more efficient estimation and compensation techniques and hardware implementation.

The future work in this area may consider [57, 61, 63, 64] as baseline research work and further develop for more efficient estimation and compensation techniques and hardware implementation.

At the same time, (i) improvements in the a posteriori error bounds for nonaffine problems [38]; (ii) reduction of the complexity of the parametrized operators and more efficient estimation of lower bounds of stability factors (that is, coercivity or inf-sup constants) for complex nonaffine problems [86]; or (iii) more specialized RB spaces [87] are under investigation.

This led to more efficient estimation of associations of the prognostic variables of main interest.

We present a series of computational optimizations for more efficient estimation of the likelihood function on large-scale phylogenetic problems.

In this case, the points that fell outside the upper boundary after regression were discarded, since this procedure has been shown to give a more efficient estimation [ 31].

By doing this, we expanded the number of data points for parameter estimation which allowed more efficient estimation and our use of GLM means it may be fitted in standard software.

Furthermore, the high frequency follow-up in this unique Danish dataset has allowed us to fit a more sophisticated model, which we believe leads to more efficient estimation of the rate of lung function decline in Denmark [ 6].