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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
Write a c++ program to find the sum of 0.123 ? 103 and 0.456 ? 102 and write the result in three significant digits
Glejser test is the test for the heteroscedasticity in the error terms of the regression analysis which involves regressing the absolute values of the regression residuals for the
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
A law supposedly applicable to voting behaviour which has a history of several decades. It may be stated thus: Consider a two-party system and suppose that the representatives of t
Play-the-winner rule is a process sometimes considered in the clinical trials in which the response to treatment is positive (a success) or negative (a failure). One of two treatm
Confidence profile method : A Bayesian approach to meta-analysis in which the information in each piece of the evidence is captured in the likelihood function which is then used al
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
Dear Experts, Please note that I''m doing a PhD in Business management under the title: Technology transfer and competitive advantage in Qatar oil and gas companies. It is a quant
Observation-driven model is a term generally applied to models for the longitudinal data or time series which introduce within the unit correlation by specifying the conditional
Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig
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