long memory parameter estimation
Wavelet estimation of the long memory parameter for Hermite polynomial of Gaussian processes
... The paper is structured as follows. In Section 2 we introduce the wavelet filters and state the assumptions imposed on them. In Section 3 we state our main result and we introduce the Rosenblatt process which appears as ...
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Application of Malliavin calculus and analysis on Wiener space to long-memory parameter estimation for non-Gaussian processes
... Using multiple Wiener-It^ o stochastic integrals and Malliavin calculus we study the rescaled quadratic variations of a general Hermite process of order q with long-memory (Hurst) parameter H 2 ( 1 2 ...
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On the spectral density of the wavelet coefficients of long memory time series with application to the log-regression estimation of the memory parameter
... co-authors for studying Fourier estimators. For the wavelet estimator defined above, these quantities depend primarily on n and on the scale index J 0 , while in the Fourier case, the bounds are generally expressed as ...
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Marginal density estimation for linear processes with cyclical long memory
... of long memory: one regular and the other cyclical according to whether the spectral density has a pole at the origin or outside the ...the long memory parameter have been adapted to ...
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Analysis of stationary and non-stationary long memory processes : estimation, applications and forecast
... alia, Geweke and Porter-Hudak (1983), Fox and Taqqu (1986), Sowell (1992), Robin- son (1992)). However, most of them lack power when used for testing purposes. On one hand, the semiparametric techniques tend to yield ...
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Estimation of the Memory Parameter of the Infinite Source Poisson Process
... The long- range dependence property has motivated many empirical studies of internet traffic and theoretical ones concerning its impact on queuing (these questions are studied in the M/G/ ∞ case in Parulekar and ...
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Bayesian nonparametric estimation of the spectral density of a long memory Gaussian time series
... 4 Computational issues Any practical implementation of our nonparametric approach must take into account the fact that the computation of the likelihood function in this context is very expensive since both the ...
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Estimating long memory in volatility
... semiparametric estimation of the memory parameter in a model which in- cludes as special cases both the long-memory stochastic volatility (LMSV) and fractionally integrated exponential ...
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Log-average periodogram estimator of the memory parameter
... the memory parameter estimate of a long-memory ...The estimation method follows the GPH procedure, where the periodogram is replaced by the averaged periodogram in the regression ...
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Bayesian nonparametric estimation of the spectral density of a long or intermediate memory Gaussian process
... For instance, under the representation f (λ) = |λ| −2d g(|λ|), one would like to estimate d as a measure of long-range dependence, without resorting to parametric assumptions on the nuisance parameter g; ...
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Central limit theorem for the robust log-regression wavelet estimation of the memory parameter in the Gaussian semi-parametric context
... Introduction Long-range dependent processes are characterized by hyperbolically slowly decaying cor- relations or by a spectral density exhibiting a fractional pole at zero ...decades, long-range dependence ...
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Marginal density estimation for linear processes with cyclical long memory
... of long memory: one regular and the other cyclical according to whether the spectral density has a pole at the origin or outside the ...the long memory parameter have been adapted to ...
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Locally stationary long memory estimation
... varying parameter of a locally stationary short memory process, see [20], or, in a more general fashion, Example ...of long memory in [3] seems not to affect the estimation ...local ...
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Detection of non-constant long memory parameter
... (multiple) estimation of d which is not very accurate if the number of observations between two change-points is not large enough; moreover, estimates of d involve band- width or some other tuning parameters and ...
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On fixed-time parameter estimation under interval excitation
... on estimation off- line): the linear least squares, the maximum-likelihood estimation, the Bayesian linear regression, the principal component regression [1], [2], to mention a ...line estimation ...
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Does long-term memory affect refreshing in verbal working memory?
... reduce refreshing opportunities (by introducing a con- current task, or increasing its pace) would replicate well-known effects and would, thus, lead to a reduction of recall performance (e.g., Barrouillet et al., 2004, ...
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Long Short-Term Memory Neural Equalizer
... In this paper, we propose a novel approach based on the long short-term memory neural network and deep learning for channel signal equalization. In many circumstances, neu- ral network computing is software ...
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Aggregation and long memory: recent developments
... Perilio˘ glu and Puplinskait˙e (2013), following the characterization studied in Mikosch and Samorodnitsky (2000). All these results agree with the above characterization in terms of the partial sums process, in the ...
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Computable lower bounds for deterministic parameter estimation
... Ratio Estimation: MSE conditioned or not by the Energy Detector versus SNR, P F A = 10 −4 where it plays a crucial role in selecting instances with relatively high signal energy - sufficient to exceed the ...
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Primal-Dual Formulations for Parameter Estimation Problems
... Unité de recherche INRIA Lorraine, Technopôle de Nancy-Brabois, Campus scientifique, 615 rue du Jardin Botanique, BP 101, 54600 VILLERS LÈS NANCY Unité de recherche INRIA Rennes, Irisa, [r] ...
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