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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.
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Range is the difference between the largest and smallest observations in the data set. Commonly used as an easy-to-calculate measure of the dispersion in the set of observations b
how does it work exactly
Censored observations : An observation xi on some variable of interest is consired to be censored if it is known that xi Li (left-censored)or xi Ui (right-censored) where Li and Ui
Pattern recognition is a term for a technology that recognizes and analyses patterns automatically by machine and which has been used successfully in many areas of application inc
Bayesian confidence interval : An interval of the posterior distribution which is so that the density of it at any point inside the interval is greater than that of the density at
A comprehensive regression analysis of the case study London has been carried out to test the 4 assumptions of regression: 1. Variables are normally distributed 2. Linear rel
Hill-climbing algorithm is an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizin
The scatter plots of SRES1, RESI1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plots sho
Bayesian inference : An approach to the inference based largely on Bayes' Theorem and comprising of the below stated principal steps: (1) Obtain the likelihood, f x q describing
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