Differencing as an approximate de-trending device /

Differencing as an approximate de-trending device /

Consider the model yj = f(j/n) + [var epsilon]j, j = 1,..., n, where the yj's are observed, f is a smooth but unknown function, and the [var epsilon]j's are unobserved errors from a zero mean, strictly stationary process. The problem addressed is that of estimating the covariance function...

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Bibliographic Details
Main Author: Hart, Jeffrey D. (Author)
Corporate Author: United States. Office of Naval Research (sponsoring body.)
Format: Book
Language:English
Published: College Station, Texas : Department of Statistics, Texas A & M University, [1989]
Series:Technical report (Texas A & M University. Department of Statistics) ; no. 36.
Subjects:
Time-series analysis.
Analysis of covariance.
Estimation theory.
Stationary processes.
Kernel functions.
Fourier series.
Nonparametric statistics.
Regression analysis.
Mathematical statistics.
Statistics > Nonparametric inference > Estimation.
Statistics > Nonparametric inference > Nonparametric regression.
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Cushing: Texas A&M Publications (Remote Storage: 2-3 day retrieval)

Holdings details from Cushing: Texas A&M Publications (Remote Storage: 2-3 day retrieval)
Call Number: QA276.A12 T4 no.36
 
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QA276.A12 T4 no.36 Available