Conditional Means and Covariances of Normal Variables with Singular Covariance Matrix Export

@article{citeulike:3209935, abstract = {This note gives formulas for conditional means and covariances--formulas which are valid even when the joint distribution is singular. The method is algebraic; it applies to any joint distribution for which independence and zero correlation are equivalent.}, author = {Marsaglia, George}, citeulike-article-id = {3209935}, citeulike-linkout-0 = {http://dx.doi.org/10.2307/2282635}, citeulike-linkout-1 = {http://www.jstor.org/stable/2282635}, doi = {10.2307/2282635}, issn = {01621459}, journal = {Journal of the American Statistical Association}, keywords = {multivariate, normal, regression}, number = {308}, pages = {1203--1204}, posted-at = {2008-09-09 13:49:29}, priority = {2}, publisher = {American Statistical Association}, title = {Conditional Means and Covariances of Normal Variables with Singular Covariance Matrix}, url = {http://dx.doi.org/10.2307/2282635}, volume = {59}, year = {1964} }

TY - JOUR ID - citeulike:3209935 L3 - citeulike-article-id:3209935 N2 - This note gives formulas for conditional means and covariances--formulas which are valid even when the joint distribution is singular. The method is algebraic; it applies to any joint distribution for which independence and zero correlation are equivalent. IS - 308 JF - Journal of the American Statistical Association SN - 01621459 EP - 1204 TI - Conditional Means and Covariances of Normal Variables with Singular Covariance Matrix PB - American Statistical Association VL - 59 SP - 1203 KW - multivariate KW - normal KW - regression AU - Marsaglia, George PY - 1964/// UR - http://dx.doi.org/10.2307/2282635 ER -