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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.
Identification keys: The devices for identifying the samples from a set of known taxa, which contains a tree- structure where each node corresponds to the diagnostic question of t
Window variables are the variables measured during the constrained interval of an observation period which is accepted as the proxies for the information over the whole period. Fo
The statistical methods for estimation and inference which are based on a function of sample observations, probability distribution of which does not rely upon a complete speci?cat
Marginal matching is the matching of the treatment groups in terms of means or other summary characteristics of matching variables. This has been shown to be almost as efficient a
Martingale: In the gambling context the term at first referred to a system for recouping losses by doubling the stake after each loss has occured. The modern mathematical concept
Probability distribution : For the discrete random variable, a mathematical formula which provides the probability of each value of variable. See, for instance, binomial distributi
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What is statistical inference? Statistical inference can be defined as the method of drawing conclusions from data which are subject to random variations. This is based o
need answers to questions in book advanced and multivariate statistical methods
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