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Maximum likelihood estimation is an estimation procedure involving maximization of the likelihood or the log-likelihood with respect to the parameters. Such type of estimators is particularly important because of their many desirable statistical properties such as consistency, and asymptotic efficiency. As an example considers the number of successes, X, in a sequence of random variables from a Bernoulli distribution with success probability p. The likelihood can be given by differentiating the log-likelihood, L, with respect to p gives the following
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Tree is the term from the branch of the mathematics which known as the graph theory, used to describe any set of the straight-line segments joining the pairs of points in some pro
Multivariate analysis of variance is the procedure for testing equality of the mean vectors of more than two populations for the multivariate response variable. The method is dire
Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig
Paired samples are the two samples of the observations with the characteristic feature with each of the observation in one sample have only one matching observation in the other s
Persson Rootze ´n estimator is an estimator for the parameters in the normal distribution when the sample is truncated so that all the observations under some fixed value C are re
Non linear mapping (NLM ) is a technique for obtaining a low-dimensional representation of the set of multivariate data, which operates by minimizing a function of the differences
Interval-censored observations are the observations which often occur in the context of studies of time elapsed to the particular event when subjects are not monitored regularl
what is measures of variability?
2 jobs n machines,graphical method,how to determine which job should proceed first on each machine
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