Ecme algorithm, Advanced Statistics

Assignment Help:

The Expectation/Conditional Maximization Either algorithm which is the generalization of ECM algorithm attained by replacing some of the CM-steps of ECM which maximize the constrained expected complete-data log-likelihood, with steps that maximize correspondingly constrained real likelihood. The algorithm can have substantially faster convergence rate than either the EM algorithm or ECM measured using either the number of iterations or actual computer time. There are two reasons for this enhancement. First, in some of the ECME's maximization steps the actual likelihood is being conditionally maximized, rather than the current approximation to it as with EM and ECM. Second,

ECME permits faster converging numerical techniques to be used on only those constrained maximizations where they are most efficacious.

 


Related Discussions:- Ecme algorithm

Degenerate distributions, The special cases of the probability distribution...

The special cases of the probability distributions in which the random variable's distribution is concentrated at one point only. For instance, a discrete uniform distribution when

Behrens fisher problem, Behrens Fisher problem : The difficulty of testing ...

Behrens Fisher problem : The difficulty of testing for the equality of the means of the two normal distributions which do not have the equal variance. Various test statistics have

Homoscedasticity - reasons for screening data, Homoscedasticity - Reasons f...

Homoscedasticity - Reasons for Screening Data Homoscedasticity is the assumption that the variability in scores for a continuous variable is roughly the same at all values of

Tests for heteroscedasticity, The Null Hypothesis - H0: There is no heteros...

The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1:  There is heteroscedasticity i.e. β 1 0 Reject H0 if nR2 > MTB >

Quasi-experiment, Quasi-experiment is a term taken in use for studies whic...

Quasi-experiment is a term taken in use for studies which resemble experiments but are weak on some of the characteristics, particularly that allocation of the subjects to groups

Factor, The term used in a variety of methods in statistics, but mostly to ...

The term used in a variety of methods in statistics, but mostly to refer to the categorical variable, with a less number of levels, under examination in an experiment as a possible

Half-normal plot, Half-normal plot is a  plot for diagnosing the model inad...

Half-normal plot is a  plot for diagnosing the model inadequacy or revealing the presence of outliers, in which the absolute values of, for instance, the residuals from the multipl

Petersen''s factor theorem, Suppose the graph G is n-connected, regular of ...

Suppose the graph G is n-connected, regular of degree n, and has an even number of vertices. Prove that G has a one-factor. Petersen's 2-factor theorem (Theorem 5.40 in the note

Multilevel models, Multilevel models are the regression models for the mul...

Multilevel models are the regression models for the multilevel or clustered data where units i are nested in the clusters j, for example a cross-sectional study where students are

Alternative hypothesis, The Null Hypothesis - H0: β0 = 0, H0: β 1 = 0, H...

The Null Hypothesis - H0: β0 = 0, H0: β 1 = 0, H0: β 2 = 0, Β i = 0 The Alternative Hypothesis - H1: β0 ≠ 0, H0: β 1 ≠ 0, H0: β 2 ≠ 0, Β i ≠ 0      i =0, 1, 2, 3

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd