Displaying similar documents to “Some results on the spectral analysis of nonstationary time series.”

Testing a sub-hypothesis in linear regression models with long memory covariates and errors

Hira L. Koul, Donatas Surgailis (2008)

Applications of Mathematics

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This paper considers the problem of testing a sub-hypothesis in homoscedastic linear regression models when the covariate and error processes form independent long memory moving averages. The asymptotic null distribution of the likelihood ratio type test based on Whittle quadratic forms is shown to be a chi-square distribution. Additionally, the estimators of the slope parameters obtained by minimizing the Whittle dispersion is seen to be n 1 / 2 -consistent for all values of the long memory...

On spectral bandwidth of a stationary random process

Vladimír Klega (1983)

Aplikace matematiky

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The irregularity coefficient is one of the numerical characteristics of the spectral bandwith of a stationary random process. Its basic properties are investigated and the application to the dichotomic classification of a process into narrow-band and wide-band ones is given. Further, its behaviour is analyzed for sufficiently wide classes of stationary processes whose spectral densities frequently appear both in theory and applications.

Weakly stationary processes with non–positive autocorrelations

Šárka Došlá, Jiří Anděl (2010)

Kybernetika

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We deal with real weakly stationary processes { X t , t ∈ ℤ } with non-positive autocorrelations { r k } , i. e. it is assumed that r k ≤ 0 for all k = 1 , 2 , ⋯ . We show that such processes have some special interesting properties. In particular, it is shown that each such a process can be represented as a linear process. Sufficient conditions under which the resulting process satisfies r k ≤ 0 for all k = 1 , 2 , ⋯ are provided as well.