Abstract
When two random variables are bivariate normally distributed Stein's original lemma allows to conveniently express the covariance of the first variable with a function of the second. Landsman and Neslehova (2008) extend this seminal result to the family of multivariate elliptical distributions. In this paper we use the technique of conditioning to provide a more elegant proof for their result. In doing so, we also present a new proof for the classical linear regression result that holds for the elliptical family.
| Original language | English |
|---|---|
| Pages (from-to) | 2016-2022 |
| Number of pages | 7 |
| Journal | Journal of Statistical Planning and Inference |
| Volume | 143 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - Nov 2013 |
Keywords
- Conditional expectation
- Multivariate elliptical distribution
- Siegel's formula
- Stein's lemma
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Applied Mathematics
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