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Network sampling is a sampling design in which the simple random sample or strati?ed sample of the sampling units is made and all observational units which are linked to any of the selected sampling units are taken. Different observational units might be linked to different numbers of sampling units. In the survey for estimation of the prevalence of a rare disease, for instance, a random sample of medical centers may be chosen. From the records of each medical centre in sample, records of the patients who are treated for the disease of interest could be extracted. A given patient might have been treated at more than one centre and the more centers at which the treatment has been taken, the higher the inclusion probability for the patient's records.
how to find the PDF and CDF of a gamma random variable with given equation?
Biplots: It is the multivariate analogue of the scatter plots, which estimates the multivariate distribution of the sample in a few dimensions, typically two and superimpose on th
This term is sometimes used for the data collected in those longitudinal studies in which more than the single response variable is recorded for each subject on each occasion. For
Occam's razor is an early statement of the parsimony principle, which was given by William of Occam (1280-1349) namely 'entia non sunt multiplicanda praeter necessitatem'; which m
What is the EM?
Computer-intensive methods : The statistical methods which require almost identical computations on the data repeated number of times. The term computer intensive is, certainly, a
This is an approach to the modelling of time-frequency surfaces which consists of a Bayesian regularization scheme in which the prior distributions over the time-frequency coeffici
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
A unified approach to all problems of prediction, estimation, and hypothesis testing. It is based on concept of the decision function, which tells the performer of experiment how t
Quantile regression is an extension of the classical least squares from estimation of the conditional mean models to the estimation of the variety of models for many conditional q
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