Sentence examples for multiple starting values from inspiring English sources

This greatly limits the usefulness of the approach due to the computational effort required to examine multiple starting values.

Therefore, we suggest re-examining variants with final estimates on these boundaries using multiple starting values for the EM algorithm to increase the chance of finding the global maximum and possibly further improve estimates and genotype-call error rates.

It is important to note that although introducing multiple starting values for the EM algorithm (which is recommended for markers converging to estimates on the boundaries p = 0 or 1 or α = 0) is likely to improve the overall chance of locating a global optimum, such a strategy still does not guarantee proper estimates in uninformative data.

We used multiple start values to avoid convergence on local maxima [ 34] and assumed a missing at random mechanism (MAR), i.e. missingness depends on the observed components of the complete data and not on missing data [ 56].

To prevent ending up with a local solution, multiple sets of starting values are used.

Thus, we used multiple sets of different starting values as recommended by [ 33, 37].

The Latent Gold estimation involves multiple sets with random starting values to avoid local maxima.

The MCMC algorithm convergence was assessed by checking the stabilisation of the plots of iterate parameter value, after a given number of samples and by running multiple chains from dispersed starting values.

For the analyses presented in this paper, inferences were based on 105,000 iterations after discarding an initial burn-in of 5,000 iterations, with convergence assessed by running multiple chains from various starting values [ 28].

As a useful tool we suggest the use of the R rotine multiStart of R package BB (for solving and optimizing large-scale nonlinear systems) for dealing with multiple starting points to obtain multiple solutions and to test sensitivity to starting values.

Multiple runs were carried out with different starting values to check for convergence in all analyses.