Titlebook: Stationary Sequences and Random Fields; Murray Rosenblatt Book 1985 Birkh?user Boston, Inc. 1985 Banach Space.Hilbert space.Likelihood.Max

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978-0-8176-3264-9Birkh?user Boston, Inc. 1985

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Density and Regression Estimates,les. Our object is not that of generality, rather that of understanding. Later on, it will be seen that there are counterparts of these results for independent identically distributed random variables in the domain of suitably restricted stationary processes.

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Stationary Processes,ose covariance function depends only on the difference in the times at which the observations are made. The importance of this assumption is due to the fact that it implies that a Fourier (or harmonic) analysis of both the covariance function and the process itself can be carried out. These results

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Quadratic Forms, Limit Theorems and Mixing Conditions,e estimates under appropriate conditions when sampling from a stationary process. Related quadratic forms are also considered. For this, we need to derive appropriate types of central limit theorems that will be employed in this chapter as well as in derivations in later chapters. However, in most c