regressor's Usage Examples:

A positive covariance of the omitted variable with both a regressor and the dependent variable will lead the OLS estimate of the included.

standardization is done only with respect to the standard deviation of the regressor (the independent variable x {\displaystyle x} ).

constant term in all regression equations is a coefficient multiplied by a regressor equal to one.

in regression analysis, a design matrix, also known as model matrix or regressor matrix and often denoted by X, is a matrix of values of explanatory variables.

with time-varying regressors is estimating the effect of unemployment insurance on unemployment spells.

Pyrrho"s lemma is the result that if one adds just one extra variable as a regressor from a suitable set to a linear regression model, one can get any desired.

Given a single regressor, relative simplicity can be defined by specifying q i {\displaystyle q_{i}}.

)x_{t}^{(m)}+\varepsilon _{t}^{(m)},} where y is the dependent variable, x is the regressor, m denotes the frequency – for instance if y is yearly x t ( 4 ) {\displaystyle.

,Xk} are regressor-variables (“affecting factors”) that deliver systematic variation to the.

assuming proportionality between error term variance and the square of the regressor, suggested instead that analysts "assume a structure for the variance.

estimate or generate regressors from observable data.

Including a lagged dependent variable as a regressor violates strict exogeneity, because the lagged dependent variable is likely.

This generated regressor method is also applicable to unobserved instrumental variables.