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This is extension of the EM algorithm which typically converges more slowly than EM in terms of the iterations but can be much faster in the whole computer time. The general idea of the algorithm is to replace M-step of each EM iteration with the sequence of S >1conditional or constrained maximization or the CM-steps, each of which maximizes the expected complete-data log-likelihood found in the previous E-step subject to constraints on parameter of interest, θ, where the collection of all the constraints is such that the maximization is over the full parameter space of θ. Because the CM maximizations are over the smaller dimensional spaces, many times they are simpler, faster and more reliable than corresponding full maximization known in the M-step of the EM algorithm.
wat iz z difference b/n logistic regression and multiple regression analysis /
The procedure which targets to use the health and health-related data which precede diagnosis and/or confirmation to identify possible outbreaks of the disease, mobilize a rapid re
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 constrai
You may have the opportunity to buy some electronic components. These components may be reliable (1) or unreliable (2). The potential pro?ts are £10,000 if the components are rel
Continual reassessment method: An approach which applies Bayesian inference for determining the maximum tolerated dose in a phase I trial. The method starts by assuming a logistic
The results of a survey determined whether the age of a driver 21 years and older has any effect on the number of motor vehicle accidents in which he/she is involved. Question 1:
Uncertainty analysis is the process for assessing the variability in the outcome variable that is due to the uncertainty in estimating the values of input parameters. A sensitivit
Surveys which use lists related with the vital statistics to sample individuals for the further information. For instance, the 1988 National Mortality Follow back Survey sampled de
Huffman code is used to compress data file, where the data is represented as a sequence of characters. Huffman's greedy algorithm uses a table giving how often each character occur
The model which is applicable to the longitudinal data in which the dropout process might give rise to the informative lost values. Specifically if the study protocol specifies the
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