linear models

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linear models, statistical models in which the value of a parameter for a given value of a factor is assumed to be equal to
a +
bx, where
a and
b are constants. The models predict a linear regression.
References in periodicals archive ?
Extending the Linear Model With R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, 2nd Edition (online access included)
Keywords: Linear models Ordinary least square Method Recursive Test
The interval model was obtained from 29 linear models which were identified from step responses.
The linear model used in our study is Spearman's factor analysis (FA) model, usually known as the congeneric model in the psychometric literature (Joreskog, 1971).
After the logistic regression model Poisson regression is the most widely used generalized linear models.
Generalized linear models require a huge amount of data that small carriers do not have.
The differences in the ASTM D245 formulas for pieces of different dimensions indicate that slightly different linear models are being used in each case.
linear models [1,9], non-linear models [2,3], probabilistic techniques [5], tensor principal component analysis [8], tensor discriminant analysis [6], Tucker decomposition [7], and correlation tensor analysis [4]).
ABSTRACT : Studies to detect genes responsible for economic traits in farm animals have been performed using parametric linear models.
Some alternative proofs were given: Seely [27], [28] restricted the choiee of the BLUE of E(y) to a finite-dimensional linear space; Drygas [11], [12] dealt with conditions under which the BLUE of [micron] is independent on V for multivariate linear models in locally convex topological vector space; Beganu [5], [7], [10] considered the existence conditions of the BLUE for the fixed effects in multivariate mixed linear models; Qian and Tian [22] established some properties for the BLUE of a subset of regression coefficients in general linear model.
The techniques outlined in this chapter are then used to develop methods for validating the appropriate statistical model in the chapters on Multiple Linear Regression, Exploiting the Linear Model Framework, and Logistic Regression and Other Generalized Linear Models.
Our texbooks abound with linear models of communication--starting with a sender on the left, ending with a receiver on the right.