Sentence examples for information likelihood from inspiring English sources

The entire system of the equations is jointly estimated by full information likelihood method.

By combining the sample information (likelihood function) and the smoothness information (smooth prior distribution) in the Bayes' theorem, the influence of statistical fluctuations is effectively removed, and greatly improved estimation can be obtained by maximizing the posterior probability.

By combining the sample information (likelihood function) and the smoothness information (smooth prior distribution) in the Bayes' theorem, the influence of statistical fluctuations is effectively removed, and greatly improved estimation, which is close to the true distribution, can be obtained by maximizing the posterior probability.

To summarize, in this model, assigned fragment abundances are defined as asymptotically multivariate normal and an accompanying variance-covariance matrix is obtained from the inverse of the Fisher information likelihood matrix.

Our approach to the analyses is guided by our own experience, 56 and recent reviews of the relative advantages of constrained full information likelihood treatment of the outcome versus inclusion of the baseline value as a covariate in ANCOVA, 57 and methods of estimation (generalised estimating equations (GEE) vs mixed random effects).

This was done by fitting a fully saturated model using full information likelihood to the data of twins in five sex-by-zygosity groups: monozygotic male twin pairs (MZM), dizygotic male twin pairs (DZM), monozygotic female twin pairs (MZM), dizygotic female twin pairs (DZM) and dizygotic twin pairs of opposite sex (DOS; if available in the particular cohort).

Comparisons are also made to a full information likelihood-based procedure that is only feasible to compute when limited follow-up observations are available.

Given a sufficiently large sample size an arbitrarily large number of bins could be used for estimating mutual informations and likelihood ratios, eliminating information loss due to binning.

Without such information, the likelihood of stopping a disease with targeted drugs is small.The story of another targeted molecule, Iressa, illustrates that point.

full information maximum likelihood.

The full information maximum likelihood method (FIML) was likewise applied (e.g. Enders 2006).