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Dependence Measuring from Conditional Variances

100%

Kamnitui N., Santiwipanont T., Sumetkijakan S.

Dependence Modeling

2015

tom 3

nr 1

A conditional variance is an indicator of the level of independence between two random variables. We exploit this intuitive relationship and define a measure v which is almost a measure of mutual complete dependence. Unsurprisingly, the measure attains its minimum value for many pairs of non-independent ran- dom variables. Adjusting the measure so as to make it invariant under all Borel measurable injective trans- formations, we obtain a copula-based measure of dependence v* satisfying A. Rényi’s postulates. Finally, we observe that every nontrivial convex combination of v and v* is a measure of mutual complete dependence.

Estimators of g-monotone dependence functions

86%

Krajka A.

Applicationes Mathematicae

1998-1999

tom 25

nr 3

253-269

The notion of g-monotone dependence function introduced in [4] generalizes the notions of the monotone dependence function and the quantile monotone dependence function defined in [2], [3] and [6]. In this paper we study the asymptotic behaviour of sample g-monotone dependence functions and their strong properties.

Ograniczanie wyników

1 Applicationes Mathematicae

1 Dependence Modeling

1 Kamnitui N.

1 Krajka A.

1 Santiwipanont T.

1 Sumetkijakan S.

1 2015

1 1998

Wyniki wyszukiwania

Dependence Measuring from Conditional Variances

Estimators of g-monotone dependence functions