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Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is most in agreement with the data configuration. For instance, for the bivariate data, y1,y2, if the quadratic coordinate system is sought, a variable z is defined as given below: with the coefficients being set up so that the variance of z is a maximum amongst all such quadratic functions of y1 and y2.
Respondent-driven sampling (RDS ): The form of snowball sampling which starts with the recruitment of the small number of people in the target population to serve as the seeds. Aft
It is an informal method of assessing the effect of the publication bias, generally in the context of the meta-analysis. The effect measures from each of the reported study are plo
A term usually used for unobserved individual heterogeneity. Such variation is of main concern in the medical statistics particularly in the analysis of the survival times where ha
Hurdle Model: The model for count data which postulates two processes, one generating the zeros in the data and one generating positive values. The binomial model decides the bina
Opreation research phase
The problematic and enigmatic theory of an inference introduced by the Fisher, which extracts a probability distribution for the parameter on the basis of the data without having f
The act of combining data from heterogeneous sources with the intent of extracting information that would not be available for any single source in isolation. An example is the com
In the time series plot and scatter graphs there were many outliers that were clearly visible. These have been removed to identify if they were influential or had high leverage and
Balanced incomplete repeated measures design (BIRMD): An arrangement of the N randomly selected experimental units and k treatments in which each and every unit receives k1 treatm
Your first task is to realize two additional data generation functions. Firstly, extend the system to generate random integral numbers based on normal distribution. You need to stu
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