
Identifiability of twocomponent skew normal mixtures with one known component
We give sufficient identifiability conditions for estimating mixing prop...
read it

Wasserstein distance error bounds for the multivariate normal approximation of the maximum likelihood estimator
We obtain explicit Wasserstein distance error bounds between the distrib...
read it

Extremal properties of the multivariate extended skewnormal distribution
The skewnormal and related families are flexible and asymmetric paramet...
read it

Calculations involving the multivariate normal and multivariate t distributions with and without truncation
This paper presents a set of Stata commands and Mata functions to evalua...
read it

On the Le Cam distance between multivariate hypergeometric and multivariate normal experiments
In this short note, we develop a local approximation for the logratio o...
read it

Maximal skewness projections for scale mixtures of skewnormal vectors
Multivariate scale mixtures of skewnormal (SMSN) variables are flexible...
read it

Unconstrained representation of orthogonal matrices with application to common principle components
Many statistical problems involve the estimation of a (d× d) orthogonal ...
read it
On the Conditional Distribution of a Multivariate Normal given a Transformation  the Linear Case
We show that the orthogonal projection operator onto the range of the adjoint of a linear operator T can be represented as UT, where U is an invertible linear operator. Using this representation we obtain a decomposition of a Normal random vector Y as the sum of a linear transformation of Y that is independent of TY and an affine transformation of TY. We then use this decomposition to prove that the conditional distribution of a Normal random vector Y given a linear transformation TY is again a multivariate Normal distribution. This result is equivalent to the wellknown result that given a kdimensional component of a ndimensional Normal random vector, where k<n, the conditional distribution of the remaining (nk)dimensional component is a (nk)dimensional multivariate Normal distribution, and sets the stage for approximating the conditional distribution of Y given g(Y), where g is a continuously differentiable vector field.
READ FULL TEXT
Comments
There are no comments yet.