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Misspecification is the term is applied to describe the assumed statistical models which are incorrect for one of the several of reasons, for instance, using the wrong probability distribution, omitting significant covariates, or using wrong link function. Such type of errors can produce inconsistent or inefficient estimates of the parameters
Partial least squares is an alternative to the multiple regressions which, in spite of using the original q explanatory variables directly, constructs the new set of k regressor v
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Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models. This will be very
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
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Invariant transformations to combine marginal probability functions to form multivariate distributions motivated by the need to enlarge the class of multivariate distributions beyo
Indirect least squares: An estimation technique used in the fitting of structural equation models. Commonly least squares are first used to estimate reduced form parameters. Usi
The term which is used in the industrial experimentation, where there is commonly a large set of candidate factors believed to have the possible significant influence on the respon
Residual plots are the plots of some type of residual which might be helpful in assessing the assumption made by the fitted model. In regression analysis there are various method
The graphic representation of the alternatives in a decision making problem which summarizes all the possibilities foreseen by the decision maker. For instance, suppose we are give
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