Asymptotic theory of conditional inference for stochastic processes
This paper develops an approach to conditional inference for nonergodic stochastic process models by considering asymptotic properties. The context for most of the analysis is that of \textit{L. Le Cam}'s local asymptotic theory [Proc. 6th Berkeley Sympos. Math. Statist. Probab., Univ. Calif. 1970, 1, 245-261 (1972; Zbl 0271.62004)], in particular, the locally asymptotically mixed normal (LAMN) situation. An attempt has been made to evaluate local asymptotic properties of global procedures.
scientific article; zbMATH DE number 3988543
scientific article