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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.
Over dispersion is the phenomenon which occurs when empirical variance in the data exceeds the nominal variance under some supposed model. Most often encountered when the modeling
Kurtosis: The extent to which the peak of the unimodal probability distribution or the frequency distribution departs from its shape of the normal distribution, by either being mo
Grade of membership model: This is the general distribution free method for the clustering of the multivariate data in which only categorical variables are included. The model ass
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
Assume that a population is normally distributed with a mean of 100 and a standard deviation of 15. Would it be unusual for the mean of a sample of 20 to be 115 or more?
The Null Hypothesis - H0: β0 = 0, H0: β 1 = 0, H0: β 2 = 0, Β i = 0 The Alternative Hypothesis - H1: β0 ≠ 0, H0: β 1 ≠ 0, H0: β 2 ≠ 0, Β i ≠ 0 i =0, 1, 2, 3
Product-limit estimator is a method for estimating the survival functions for the set of survival times, some of which might be censored observations. The logic behind the procedu
Minimization is the method or technique for allocating patients to the treatments in clinical trials which is usually the acceptable alternative to random allocation. The procedur
Quantalassay: The experiment in which the groups of subjects are exposed to the different doses of, generally, a drug, to which the particular number respond. Data from such type
The phrase first spoken by one of the witches in Macbeth. Now this is used to describe the exponential rise in the number of possible locations in the multivariate space as dimensi
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