Em algorithm, Advanced Statistics

Assignment Help:

The method or technique for producing the sequence of parameter estimates that, under the mild regularity conditions, converges to maximum likelihood estimator. Of particular significance in the context of the incomplete data problems. The algorithm comprises of two steps, called as the E, or
Expectation step and the M, or the Maximization step. In the previous, the expected value of log-likelihood conditional on the observed data and the current estimates of parameters are found. In the M-step, the function is maximized to provide the updated parameter estimates which increase the likelihood. The two steps are alternated until the convergence is attained. The algorithm might, in some cases, becoms very slow to converge.


This is acronym for the Epidemiological, Graphics, Estimation and Testing of the program developed for the analysis of the data from studies in epidemiology. It can be made in use for logistic regression and models might include random effects to permit over dispersion to be modelled. The beta- binomial distribution can be fitted.


Related Discussions:- Em algorithm

Artificial neural network, Artificial neural network : A mathematical arran...

Artificial neural network : A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of patte

Minimum volume ellipsoid, Minimum volume ellipsoid is a term for ellipsoid...

Minimum volume ellipsoid is a term for ellipsoid of the minimum volume which covers some specified proportion of the set of multivariate data. It is commonly used to construct rob

Graphics., how to calculate the semi average method when 8 observations are...

how to calculate the semi average method when 8 observations are given?

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

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

Describe respondent-driven sampling (rds), Respondent-driven sampling (RDS ...

Respondent-driven sampling (RDS ): The form of snowball sampling which starts with the recruitment of the small number of people in the target population to serve as the seeds. Aft

Collapsing categories, Collapsing categories : A procedure generally applie...

Collapsing categories : A procedure generally applied to contingency tables in which the two or more row or column categories are combined, in number of cases so as to yield the re

Queuing theory, 1) Let N1(t) and N2(t) be independent Poisson processes wit...

1) Let N1(t) and N2(t) be independent Poisson processes with rates, ?1 and ?2, respectively. Let N (t) = N1(t) + N2(t). a) What is the distribution of the time till the next epoch

Copulas, Invariant transformations to combine marginal probability function...

Invariant transformations to combine marginal probability functions to form multivariate distributions motivated by the need to enlarge the class of multivariate distributions beyo

Environmental statistics, The procedures used for determining how the quali...

The procedures used for determining how the quality of life is affected by the environment, in particular by factors such as air and solid wastes, water pollution, hazardous substa

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