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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 to conduct the statistical aspects of an experiment and which action to take for each possible outcome. Choosing the decision function needs a loss function to be defined which assigns numerical values to making bad or good decisions. Explicitly a general loss function is denoted by L d; expressing how bad it would be to make decision d if the parameter value were. A quadratic loss function, it could be defined as and a bilinear loss function as
Bayesian network : It is essentially an expert system in which the uncertainty is dealt with using the conditional probabilities and Bayes' Theorem. Formally such type of network c
This is extension of the EM algorithm which typically converges more slowly than EM in terms of the iterations but can be much faster in the whole computer time. The general idea o
Quincunx is the device used by Galton to illustrate his lectures, which is shown in the Figure. It had a glass face and a funnel at its top. The shot was passed through funnel an
The interplay of the genes and environment on, for instance, the risk of disease. The term represents the step away from the argument as to whether the nature or nurture is the pre
cholscores Treatment income ($000) Patient ID low Income? 0.6 Old 21.3 2 Yes 0.17 Old 27.2 13 Yes 0.69 New 27.1 16 Yes 1.09 Old 94.8
Missing values : The observations missing from the set of data for some of the reason. In longitudinal studies, for instance, they might occur because subjects drop out of the stud
What is the EM?
Institutional surveys are the surveys in which the primary sampling units are the institutions, for instance, hospitals. Within each of the sampled institution, a sample of the pa
Ordered alternative hypothesis is a hypothesis or assumption which speci?es an order for the set of parameters of interest as an alternative to the equality, rather than simply th
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >
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