(Statistics) The standard for the Ordinary Least Squares (OLS), or Regression Analysis model. The CLR Model has five basic assumptions: (1) Linearity: The dependent variable, or the variable to be explained or forecasted, can be calculated as a linear function of a specific set of independent, or explanatory variables; (2) Randomness of Disturbance Terms: The expected value of the disturbance term, that is the term showing the differences between the model's estimated values and the actual observed values, is zero; (3) Uncorrelated Disturbance Terms: The disturbance terms all have the same variance and are not correlated with each other (see Serial Correlation); (4) Data Conformity: The observations on the independent variable can be considered fixed in repeated samples, i.e., it is possible to repeat the sample with the same independent variables; (5) Sample Size and Selection: The number of observations is greater than the number of independent variables and that there are no linear relationships, i.e., no significant correlations, between the independent variables (see Multicollinearity).
CLASSICAL LINEAR REGRESSION (CLR) MODEL
Meaning of CLASSICAL LINEAR REGRESSION (CLR) MODEL in English
Environmental engineering English vocabulary. Английский словарь экологического инжиниринга. 2012