TY - JOUR
T1 - The contiguity of probability measures and asymptotic inference in continuous time stationary diffusions and Gaussian processes with known covariance
AU - Akritas, Michael G.
AU - Johnson, Richard A.
N1 - Funding Information:
Received June 25, 1979. AMS subject classification: Primary 6OJ60, 6OG15, 62E20; Secondary 62M05, 62F99. Key words and phrases: Probability measures, Gaussian processes, contiguity, asymptotic inference. * This Research supported by ONK Grant NOO014-78C-0722. ’ Now at MIT.
Funding Information:
Professor Johnson gratefully acknowledges the Wisconsin Aulumni Research Foundation for support during the period of this research.
PY - 1982/3
Y1 - 1982/3
N2 - We establish contiguity of families of probability measures indexed by T, as T → ∞, for classes of continuous time stochastic processes which are either stationary diffusions or Gaussian processes with known covariance. In most cases, and in all the examples we consider in Section 4, the covariance is completely determined by observing the process continuously over any finite interval of time. Many important consequences pertaining to properties of tests and estimators, outlined in Section 5, will then apply.
AB - We establish contiguity of families of probability measures indexed by T, as T → ∞, for classes of continuous time stochastic processes which are either stationary diffusions or Gaussian processes with known covariance. In most cases, and in all the examples we consider in Section 4, the covariance is completely determined by observing the process continuously over any finite interval of time. Many important consequences pertaining to properties of tests and estimators, outlined in Section 5, will then apply.
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U2 - 10.1016/0047-259X(82)90087-2
DO - 10.1016/0047-259X(82)90087-2
M3 - Article
AN - SCOPUS:49049132171
SN - 0047-259X
VL - 12
SP - 123
EP - 135
JO - Journal of Multivariate Analysis
JF - Journal of Multivariate Analysis
IS - 1
ER -