Sentence examples for maximum likelihood solution from inspiring English sources

Therefore, the FEMU approaches do not provide the "maximum likelihood solution".

Optimal virtual fields exist, thus minimizing the uncertainty and providing the "maximum likelihood solution".

Results confirm the success of two methods: the VFM approach which provides the "maximum likelihood solution" and the FEMU approach based on the "displacement gap" minimization.

We combine the likelihood from each sample to produce a joint likelihood for all samples together, and using initially stochastic search then directed search methods we try to identify a maximum likelihood solution.

Being an ensemble extension of variational assimilation (VAR), MLEF also offers a strong connection with the traditional single-valued forecast process through the control, or the maximum likelihood, solution.

The maximum likelihood solution finds the values (X_{q}) that maximize the probability in Eq. (7).

This method develops a dynamic programming algorithm, which is theoretically guaranteed to find exact maximum likelihood solutions of the variable order Markov chain model for haplotype inference problem within linear running time.

Then, the maximum likelihood solutions of the external parameters can be obtained by calculating the minimum value of the formula {displaystyle sum_{i=1}^m{leftVert Gleft({V}_1^{prime },{V}_2,{X}_i^{prime}right -{mme}right)-{m}_i^{prime}rightVert}^2} (6).

Assuming that there are n images in the calibration board, each image has m corner points, and all the unknown parameters' maximum likelihood solutions can be obtained by calculating the minimum value of the formula {displaystyle sum_{i=1}^n{{displaystyle sum_{j=1}^mleftVert Gleft({V}_{1 i},{V}_2,{X}_{i{V}_4,{X}_{i j}right -{m}_{i j}right -{m}}^2} (5).

The limdil function of the statmod package for R was used to find the maximum likelihood solutions of the frequencies of the CAFCs.

Any extensions of this approach so far (i.e. two-part or mixtures approaches) have been implemented using Markov Chain Monte Carlo (MCMC) methods, since maximum likelihood solutions may be difficult to obtain (Lambert et al., 2008).