Acta Geodaetica, Geophysica et Montanistica Hungarica 24. (1989)

3-4. szám - Hajagos B.–Steiner F.: Measure of the linear dependence

LINEAR DEPENDENCE 419 applicability of Eq. (1) at the end of the present paper. 2. GENERATION OF A LINEAR DEPENDENCE In the following a simplified discussion is striven at ac­cording to Einstein's principle (which refers here both to the construction of the model and to the definition and the method of determination of the measure of dependence): "whatever you do, do it in the simplest way - but even simpler do not do it". 2.1 Family of distribution types f^Cx) Let us define the family of types (supermodel) f^(x) with the parameter oC (0 < oC < 2) as follows: » КЛ­ИН-100 con. cotff.49(9 (conventional formula, Eq.1) согт. cotff. «Û0W (Eq.12) Xе • • Fig. 1. Random data pairs from a two-variable Gaussian distribution in case of independent x and y. One of the data pairs (0, 0) is burdened by a gross error. The traditional correlation coefficient is 0.989 Itl*/* Vx) = 7Г(2)

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