Maximum likelihood estimators of parameters of multidimensional stationary Gaussian AR processes (Q1323603)

This article is devoted to the estimation of the matrix \(A\) under the given stationary process \(X\), which satisfies an equation \[ dX(t) = AX(t)dt + dW(t), \] where \(\{W(t); t \geq 0\}\) is a \(k\)-dimensional standard Wiener process. The very special kind of \(A\) allows to obtain a maximum likelihood estimator for its parameters and to consider its properties.