English

Closed form expression of the multivariate standard Normal distribution under a weighted sum constraint

Probability 2018-01-22 v1

Abstract

In this letter we derive the (n1)(n-1)-dimensional distribution corresponding to a nn-dimensional i.i.d. Normal standard vector Z=(Z1,Z2,,Zn)Z=(Z_1,Z_2,\ldots,Z_n) subjected to the weighted sum constraint i=1nwiZi=c\sum_{i=1}^n w_i Z_i=c, wi0w_i\neq 0. We first address the n=2n=2 case before proceeding with the general n2n\geq 2 case. The resulting distribution is a Normal distribution whose mean vector μ\mu and covariance matrix Σ\Sigma are explicitly derived as a function of w1,,wn,cw_1,\ldots,w_n,c. The derivation of the density relies on a very specific positive definite matrix for which the determinant and inverse can be computed analytically.

Keywords

Cite

@article{arxiv.1801.06387,
  title  = {Closed form expression of the multivariate standard Normal distribution under a weighted sum constraint},
  author = {Frédéric Vrins},
  journal= {arXiv preprint arXiv:1801.06387},
  year   = {2018}
}
R2 v1 2026-06-22T23:49:51.052Z