Some statistical inferences on O-U processes
Y.S. Hsu, W.J. Park · Communication in Statistics- Theory and Methods · 1980
Let {Xkk ≥1} be a Markov Process defined on a probability space (Ω, B, Pθ) vith stationary transition probabilities where θ = (θ1θ2,…,θr) is an unknown parameter in Rr . The statistical inferences on the parameter θ have been created by many researchers (See Billings-ley [2]) and have important applications in various fields. The estimations or testing hypothesis problems on θ are usually solved based on information of one sequence of observations {X1,X2,…,Xp } from the process. In this paper we consider some statistical inference problems for θ when there are n independent sequences of observations {X1, ,X2,…,Xp} from the process under the assumption chat the process is stationary and Gaussian.