Several important properties of positive semidefinite processes of Ornstein-Uhlenbeck type are analysed. It is shown that linear operators of the form X → AX + XA T with A ∈ M d (R) are the only ones that can be used in the definition provided one demands a natural non-degeneracy condition. Furthermore, we analyse the absolute continuity properties of the stationary distribution (especially when the driving matrix subordinator is the quadratic variation of a d-dimensional Lévy process) and study the question of how to choose the driving matrix subordinator in order to obtain a given stationary distribution. Finally, we present results on the first and second order moment structure of matrix subordinators, which is closely related to the moment structure of positive semidefinite Ornstein-Uhlenbeck type processes. The latter results are important for method of moments based estimation.Keywords: completely positive matrix; matrix subordinator; normal mixture; operator self-decomposable distributions; positive semidefinite Ornstein-Uhlenbeck type process; quadratic variation; second order structure; stationary distribution with A being a d × d-matrix, L a matrix subordinator (see [3]) and the initial value Σ 0 a positive semidefinite matrix. Matrix subordinators are a generalisation of the one-This is an electronic reprint of the original article published by the ISI/BS in Bernoulli, 2009, Vol. 15, No. 3, 754-773. This reprint differs from the original in pagination and typographic detail.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.