Stationary Processes
Comparing the Time Deformation Method with the Fractional Fourier Transform in Filtering Non Stationary Processes
... stochastic processes where the frequen- cies of components do not overlap over time, but fail for those processes where the frequencies overlap over ...non-stationary processes: the ...
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On general filtering problem of stationary processes with fixed transformation
... of stationary processes, also linear filter problems is an important part of Prediction ...multidimensional stationary sequence and processes for a linear system are firsted stu- died by ...
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Optimal Multitaper Wigner Spectrum Estimation of a Class of Locally Stationary Processes Using Hermite Functions
... This paper investigates the time-discrete multitapers that give a mean square error optimal Wigner spectrum estimate for a class of locally stationary processes (LSPs). The accuracy in the estimation of the ...
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Direct and iterated multistep AR methods for difference stationary processes
... The paper focuses on the comparison of the direct and iterated AR predictors for difference stationary processes. In particular, it provides new methods for comparing the efficiency of the two predictors ...
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MAXIMUM NON-EXTENSIVE ENTROPY BLOCK BOOTSTRAP FOR NON-STATIONARY PROCESSES
... In this paper, we propose a novel entropy-based resampling scheme valid for non-stationary data. In particular, we identify the reason for the failure of the original entropy-based algorithm of Vinod and L´ ...
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On uniqueness of moving average representations of heavy tailed stationary processes
... linear processes generally admit several moving average representations, non- Gaussian linear processes have been shown to admit an essentially unique MA representation, under different regularity ...
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Direct and iterated multistep AR methods for difference stationary processes
... stationary process. In particular, it provides some useful results for comparing the efficiency of the two predictors and for extracting the trend from macroeconomic time series using the two methods. The main ...
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THE STUDY OF NON-STATIONARY PROCESSES OF THERMAL AND CHEMICAL POLLUTION OF THE BUILDING DURING THE INDUSTRIAL ACCIDENTS
... грязнения помещения при аварийном выбросе аммиака в двух местах , показанных на рис. 6, 7 показаны изолинии концентрации[r] ...
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A distance test of normality for a wide class of stationary processes
... linear processes with a Gaussian one-dimensional marginal distribution appear to be a rarity (see, ...linear processes is quite large; roughly speaking, for any stationary non-linear process, there ...
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A distance test of normality for a wide class of stationary processes
... (strictly stationary) fractionally integrated processes, which may be short-range depen- dent, long-range dependent or antipersistent depending on the value of their dependence ...
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Derivation of response spectrum compatible non-stationary stochastic processes relying on Monte Carlo-based peak factor estimation
... devoted to relating an evolutionary power spectrum (EPS) characterizing a non-stationary random process as defined by Priestley (1965) directly to a given response/design spectrum (e.g. Preumont 1985a, Spanos and ...
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Determination of non-stationary stochastic processes compatible with seismic response/design spectra
... non-stationary processes of a specific prescribed “effective duration” as is commonly defined in the field of earthquake engineering (Trifunac and Brady, ...
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Robust Extrapolation Problem for Stochastic Processes with Stationary Increments
... stochastic processes is an important part of the theory of stochastic pro- ...stochastic processes were developed by Kolmogorov [1], Wiener[2], Yaglom [3, ...non-stationary processes whose in- ...
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Spurious regressions of stationary AR(p) processes with structural breaks
... Remark 2. The heuristics for the results in Theorem 2 is rather succinct. Since the limiting behaviors of the OLS estimates are dominated by the trend components, the OLS estimates do not converge to zero, as one expects ...
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Time Frequency Domain Characterization of Stationary and Non stationary Signals
... for stationary signals Fourier transform allows us to clearly analyze the signal in its frequency transform without much ...non- stationary signals that have large frequency variations in term of sampling ...
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Unit root inference for non-stationary linear processes driven by infinite variance innovations
... variance processes, a leading example being the well-known integrated GARCH (IGARCH) and explosive GARCH models considered in Zhang, Sin and Ling ...such processes is α = 2, and so they are in the Gaussian ...
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Time-Frequency Domain Characterization of Stationary and Non stationary Signals
... for stationary signals Fourier transform allows us to clearly analyze the signal in its frequency transform without much ...non- stationary signals that have large frequency variations in term of sampling ...
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Stationary and non-stationary solutions of the evolution equation for neutrino in matter
... the stationary states and the spin-flavor coherent states of the neutrino are ...the stationary states with coefficients, which depend on the mixing angle in ...
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Have the log population processes stationary and independent increments? Empirical evidence for Italy, Spain and the USA along more than a century
... We review the classical Gibrat’s process for the population of city sizes. In particular, we are interested in whether the log-population process has stationary and independent (Gibrat’s Law for cities) ...
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Central limit theorem for stationary linear processes generated by linearly negative quadrant dependent sequence
... Note that some applications for LNQD sequence have been found. See for example, Newman [2] established the central limit theorem for a strictly stationary LNQD process. Wang and Zhang [3] provided uniform rates of ...
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