Gaussian Approximation of Conditional Elliptical Random Vectors

  title={Gaussian Approximation of Conditional Elliptical Random Vectors},
  author={Enkelejd Hashorva},
Let U d  = (U 1,…, U d )⊤, d ≥ 2 be a random vector uniformly distributed on the unit sphere of ℝ d , and let A ∊ ℝ d×d be a non-singular matrix. Consider an elliptical random vector X  = (X 1,…, X d )⊤ with stochastic representation R A ⊤ U d where the positive random radius R is independent of U d , and let X I  = (X i , i ∊ I)⊤, X J  = (X i , i ∊ J)⊤ be two vectors with non-empty disjoint index sets I, J, I ∪ J = {1,…, d}. Motivated by the Gaussian approximation of the conditional… CONTINUE READING


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