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

Forecast, The particular projection which an investigator believes is most ...

The particular projection which an investigator believes is most likely to give an accurate prediction of the future value of some process. Commonly used in the context of the anal

Define high-dimensional data, High-dimensional data : This term used for da...

High-dimensional data : This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21 st

Cluster randomization, Cluster randomization : The random allocation of the...

Cluster randomization : The random allocation of the groups or clusters of the individuals in the formation of treatment groups.Eeven though not as statistically ef?cient as the in

Dirichlet process, The distribution over distributions in the sense that ea...

The distribution over distributions in the sense that each draw from the process is itself the distribution. The name Dirichlet process or procedure is due to the fact that the ?ni

Log-linear models, Log-linear models is the models for count data in which...

Log-linear models is the models for count data in which the logarithm of expected value of a count variable is modelled as the linear function of parameters; the latter represent

Times series plots, The time series for RESI1, HI1 and COOK1 have appeared ...

The time series for RESI1, HI1 and COOK1 have appeared again with different outlier values even though the 17 outliers found early were removed.

Explain negative hyper geometric distribution, Negative hyper geometric dis...

Negative hyper geometric distribution : In sampling without replacement from the population comprising of r elements of one kind and N - r of another, if two elements corresponding

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

Develop an algebraic linear programming model, Duck Lovers Unlimited (DLU) ...

Duck Lovers Unlimited (DLU) Inc. assembles specially configured light jet aircrafts for airborne duck hunting. The quarterly demand forecasts for the upcoming fiscal year are:

Atomistic fallacy, Atomistic fallacy : A fallacy which arises because of th...

Atomistic fallacy : A fallacy which arises because of the association between two variables at the individual level might vary from the association between the same two variables m

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