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Non parametric maximum likelihood (NPML) is a likelihood approach which does not need the specification of the full parametric family for the data. Usually, the non parametric maximum likelihood is a multinomial likelihood on a sample. Simple examples comprise the empirical cumulative distribution function and the product-limit estimator. It is also used to relax the parametric assumptions regarding random effects in the multilevel models. It is losely related to the empirical likelihood.
Post stratification adjustmen t: One of the most often used population weighting adjustments used in the complex surveys, in which weights for the elements in a class are multiplie
A directed graph is simple if each ordered pair of vertices is the head and tail of at most one edge; one loop may be present at each vertex. For each n ≥ 1, prove or disprove the
An approach of using the likelihood as the basis of estimation without the requirement to specify a parametric family for data. Empirical likelihood can be viewed as the example of
An investor with a stock portfolio sued his broker, claiming that a lack of diversification in his portfolio had led to poor performance. The data, shown below, are the rates of re
distinguish the historigram and histogram
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Kolmogorov Smirnov two-sample method is a distribution free technique which tests for any difference between the two populations probability distributions. The test is relied on t
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
Prognostic scoring system is a technique of combining the prognostic information contained in the number of threat factors, in a manner which best predicts each patient's risk of
Oracle property is a name given to techniques for estimating the regression parameters in the models fitted to high-dimensional data which have the property that they can correctl
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