The realization of positive random variables via absolutely continuous transformations of measure on Wiener space.
Feyel, D., Üstünel, A.S., Zakai, M. (2006)
Probability Surveys [electronic only]
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Feyel, D., Üstünel, A.S., Zakai, M. (2006)
Probability Surveys [electronic only]
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František Straka, Josef Štěpán (1993)
Mathematica Slovaca
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Penrose, Mathew D. (2007)
Electronic Journal of Probability [electronic only]
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Zsilinszky, László (1995)
Portugaliae Mathematica
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Arturo Erdely (2017)
Kybernetika
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A dependence measure for arbitrary type pairs of random variables is proposed and analyzed, which in the particular case where both random variables are continuous turns out to be a concordance measure. Also, a sample version of the proposed dependence measure based on the empirical subcopula is provided, along with an R package to perform the corresponding calculations.
Noppadon Kamnitui, Tippawan Santiwipanont, Songkiat Sumetkijakan (2015)
Dependence Modeling
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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...
Tsirelson, Boris (2006)
Electronic Journal of Probability [electronic only]
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