Results 101 to 110 of about 4,998 (266)
The asymptotic CRLB for the spectrum of ARMA processes
IEEE Transactions on Signal Processing, 2003 This paper addresses the issue of quantifying the frequency domain accuracy of autoregressive moving average (ARMA) spectral estimates as dictated by the Cramer-Rao lower bound (CRLB). Classical work in this area has led to expressions that are asymptotically exact as both data length and model order tend to infinity, although they are commonly used in
openaire +2 more sources
Computing and estimating information matrices of weak arma models
Numerous time series admit "weak" autoregressive-moving average (ARMA) representations, in which the errors are uncorrelated but not necessarily independent nor martingale differences.
Francq, Christian +2 more
core
Robust CDF‐Filtering of a Location Parameter
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper introduces a novel framework for designing robust filters associated with signal plus noise models having symmetric observation density. The filters are obtained by a recursion where the innovation term is a transform of the cumulative distribution function of the residuals.
Leopoldo Catania +2 more
wiley +1 more source
Weak convergence of the sequential empirical processes of residuals in ARMA models
This paper studies the weak convergence of the sequential empirical process $\hat{K}_n$ of the estimated residuals in ARMA(p,q) models when the errors are independent and identically distributed.
Bai, Jushan
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Empirical‐Process Limit Theory and Filter Approximation Bounds for Score‐Driven Time Series Models
Journal of Time Series Analysis, EarlyView.ABSTRACT This article examines the filtering and approximation‐theoretic properties of score‐driven time series models. Under specific Lipschitz‐type and tail conditions, new results are derived, leading to maximal and deviation inequalities for the filtering approximation error using empirical process theory.
Enzo D'Innocenzo
wiley +1 more source
AxiomsThis paper introduces a rigorous class of two-dimensional Markov-switching autoregressive moving-average (2D MS-ARMA) models for spatial lattice data exhibiting regime-dependent dynamics.
Khudhayr A. Rashedi +3 more
doaj +1 more source
Multivariate Markov-switching ARMA processes with regularly varying noise
, 2008 The tail behaviour of stationary Rd-valued Markov-switching ARMA (MS-ARMA) processes driven by a regularly varying noise is analysed. It is shown that under appropriate summability conditions the MS-ARMA process is again regularly varying as a sequence ...
Stelzer, R., Stelzer, Robert
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Journal of Time Series Analysis, EarlyView.ABSTRACT The paper deals with the construction of a synthetic indicator of economic growth, obtained by projecting a quarterly measure of aggregate economic activity, namely gross domestic product (GDP), into the space spanned by a finite number of smooth principal components, representative of the medium‐to‐long‐run component of economic growth of a ...
Alessandro Giovannelli +2 more
wiley +1 more source
On Adaptive Estimation in Stationary ARMA Processes
The Annals of Statistics, 1987 The paper deals with adaptive construction of locally asymptotically minimax (LAM) estimators for stationary ARMA processes with independent and identically, but not necessarily normally distributed innovations. First the local asymptotic normality (LAN) for this model is proved using the sufficient conditions for LAN given by \textit{G. G. Roussas} [Z.
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ARMA spectral estimation of narrow-band processes via model reduction
, 1990 The problem of estimating autoregressive moving average (ARMA) models for narrowband processes is considered. The following approach is proposed. Estimate a high-order autoregressive (AR) approximation of the process.
Wahlberg, Bo,
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