Results in the Constitution appear in the center column; results from essays appear in the right column. Use a short, descriptive search phrase. Precise phrases like âreligious freedom,â âtaxation,â or âwomenâs suffrageâ will work better than longer phrases.
Multicollinearity refers to a situation in which two or more explanatory variables in a multiple regression model are highly linearly related. We have perfect multicollinearity if, for example as in the equation above, the correlation between two independent variables is equal to 1 or -1.In practice, we rarely face perfect multicollinearity in a data set.rom Wikipedia, the free encyclopedia. In statistics, multicollinearity (also collinearity) is a phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, meaning that one can be linearly predicted from the others with a substantial degree of accuracy.
IBM Thomas J. Watson Research Center, Yorktown Heights, New York 10598. Abstract. A three-dimensional finite difference model has been developed for the treat-. ment of saturated-unsaturated transient flow in small nonhomogeneous, anisotropic geologic. basins. The uniqueness of the model lies in its inclusion of the unsaturated zone in a basin. wide model that can also handle both confined and unconfined sâ¢aturated aquifers, under. both natural and developed conditions. The integrated equation of flow is solved by the. line successive overrelaxation technique.