Sentence examples for regularized estimates from inspiring English sources

Traditionally, STRFs have been estimated using normalized-reverse correlation (NRC), a method that uses an approximation to the stimulus covariance matrix to obtain regularized estimates.

This procedure yields regularized estimates at the end of the process.

Regularized estimates can be obtained by maximizing the penalized likelihood (3) log L P = log L - 1 2 ψ P where the penalty P is a selected function of the parameters, aimed at reducing loss in their estimates, and ψ is a tuning factor which specifies the relative emphasis to be given to the penalty compared to the unpenalized estimator.

Finally, global optimization with eSS2 is used to find the regularized estimate of the parameters.

However, there has been little interest in regularized estimation in estimating genetic parameters.

LAMs with regularized estimation therefore allow to estimate the degree of flexibility in a data-driven way.

When the regularized estimation results are compared with those from IRI-2001, JPL, CODE, UPC and ESA, best accordance is observed with JPL, UPC and CODE estimates.

Already under the assumption that the flexibility needed is the same in all components a considerable number of models needs to be estimated and compared to choose the suitable number of degrees of freedom for finite mixtures of LMs, whereas the maximum number of degrees of freedom allowed when fitting finite mixtures of LAMs using regularized estimation is less crucial.

The regularized effect estimates were used to create genetic scores for blonde hair colour, assuming an additive genetic model.

Not alike the previous literature, we propose to choose the regularization parameter by an a posteriori rule, with which we can obtain error estimate of Hölder type between the exact solution and the regularized approximation.

Furthermore, a simplified method for estimating the eigenphone matrix in case of diagonal covariance matrices is derived, and a unified framework for solving various regularized matrix estimation problems is presented.