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Kleiner Hartigan trees is a technique for displaying the multivariate data graphically as the 'trees' in which the values of the variables are coded into length of the terminal branches and the terminal branches have lengths which rely on the sums of the terminal branches they support. One significant feature of these trees which distinguishes them from most other compound characters, for instance, Chernoff's faces, is that an attempt is made to get rid of the arbitrariness of assignment of the variables by performing the agglomerative hierarchical cluster analysis of variables and using the resultant dendrogram as the foundation tree.
The model which arises in the context of estimating the size of the closed population where individuals within the population could be identified only during some of the observatio
A family of the probability distributions of the form given as here θ is the parameter and a, b, c, d are the known functions. It includes the gamma distribution, normal dis
Link functions: The link function relates the linear predictor ηi to the expected value of the data. In classical linear models the mean and the linear predictor are identical
Meta-analysis is the collection of techniques whereby the results of two or more independent studies are statistically combined to yield the overall answer to a question of intere
This is an attempt to measure the suffering caused by the illness which takes into the account both the years of the potential life lost due to the premature mortality as well as t
Attack rate : This term frequently used for the incidence of the disease or condition in the particular group, or during a limited interval of time, or under the special circumstan
Comparative exposure rate : A measure of alliance for use in a matched case-control study, de?ned as the ratio of the number of case-control pairs, where the case has greater expos
importance of time series on the number of babies given birth
Poisson regression In case of Poisson regression we use ηi = g(µi) = log(µi) and a variance V ar(Yi) = φµi. The case φ = 1 corresponds to standard Poisson model. Poisson regre
Mean squarederror is the expected value of square of the difference between an estimator and the true value of the parameter. If the estimator is unbiased then the mean of the squ
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