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Confidence estimation of the covariance function of stationary and locally stationary processes
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Mihai Giurcanu
Published/Copyright:
September 25, 2009
Summury
In this note we consider the problem of confidence estimation of the covariance function of a stationary or locally stationary zero mean Gaussian process. The constructed confidence intervals are based on the usual empirical covariance estimate and a special estimate of its variance. The results about coverage probability are stated in a nonasymptotic way and apply for small and moderate sample size under mild conditions on the model. The presented numerical results are in agreement with the theoretical issues and demonstrate applicability of the method.
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Published Online: 2009-09-25
Published in Print: 2004-04-01
© R. Oldenbourg Verlag, München
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Articles in the same Issue
- Quantization of probability distributions under norm-based distortion measures
- Confidence estimation of the covariance function of stationary and locally stationary processes
- Efficient estimation of a linear functional of a bivariate distribution with equal, but unknown, marginals: The minimum chi-square approach
- Locally asymptotically optimal tests in semiparametric generalized linear models in the 2-sample-problem
- Maximum likelihood estimator in a two-phase nonlinear random regression model
