Sentence examples for estimation implemented from inspiring English sources
The gain and loss rates were estimated using a maximum likelihood estimation implemented in the ACE (ancestral character estimation) function of the APE (analysis of phylogenetics and evolution) package (Paradis et al. 2004) in R and BayesTraits (Pagel et al. 2004).
Maximum likelihood estimation implemented by Newton-Raphson algorithm yielded optimum estimators for both the linear RIC and the nonlinear RC models.
It uses a least squares estimation implemented on the lines of the moving horizon estimation.
To estimate the fit of the model we used weighted least square mean-and-variance adjusted (WLSMV) estimation implemented in Mplus (Muthén and Muthén 1998).
Based on the nonidentical statistical assumption and accommodation of statistical parameters estimation implemented by CFAR and Burg's BWE, IBSR is more robust to noise and limitation of measurements.
All models were fitted to the data using the weighted least square mean-and-variance adjusted (WLSMV) estimation implemented in Mplus 7.31 (Muthén and Muthén 1998 2012).
To estimate the rate of synonymous (dS), non-synonymous (dN) and the dN/dS ratio for each branch of the phylogeny, we used maximum likelihood estimations implemented in the program codeml in the PAML 4.2 package [ 32].
However, the architecture is largely independent of how the global state estimation is implemented and a distributed implementation is conceivable.
If the block (b_n) belongs to a salient region and its number of contours is significant (as in Eq. 9), optical flow-based motion estimation is implemented; otherwise, we use block-based estimation.
The first-order conditional estimation method with interaction (FOCEI) and the Laplacian estimation method implemented in the software NONMEM (version 7.2, gFortran version 4.5.0, Gnu compiler collection; Supplementary Data) were used for parameter estimation.
First, the distributions of cross-validation prediction scores for negative and positive examples were estimated using kernel density estimation as implemented in R (R Development Core Team, 2008).
