Asymptotic theory of conditional inference for stochastic processes

Paul D. Feigin

Stochastic Processes and their Applications, 1986, vol. 22, issue 1, 89-102

Abstract: 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 Le Cam's local asymptotic theory: in particular, the locally asymptotically mixed normal (LAMN) situation. An attempt has been made to evaluate local asymptotic properties of global procedures.

Keywords: locally; asymptotically; mixed; normal; nonergodic; stochastic; processes; decision; theory; approximate; ancillarity; local; ancillarity; asymptotic; conditional; risk; contiguity; conditional; exponential; families (search for similar items in EconPapers)
Date: 1986
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Citations: View citations in EconPapers (1)

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