Results 271 to 280 of about 383,160 (312)

A NOTE ON THE THRESHOLD AR(1) MODEL WITH CAUCHY INNOVATIONS

Journal of Time Series Analysis, 1986
Abstract. A threshold autoregressive process of the first order with one threshold r and with Cauchy innovations is investigated in the paper. An explicit formula for the stationary density of such process is derived for the special case that r = 0 and that the autoregressive parameters have the same absolute value.
Anděl, Jiří, Bartoň, Tomáš
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Moments of AR(1)-Model Estimators

Communications in Statistics - Simulation and Computation, 2005
ABSTRACT We describe a simple technique for computing the first few moments of a large class of sample statistics related to the first-order autoregressive model with normally distributed error terms. Moments of the basic estimators of ρ and σ are then derived for illustration, also indicating how the leading term of skewness can be eliminated.
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Competitive chaotic AR(1) model estimation

Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE Signal Processing Society Workshop (IEEE Cat. No.01TH8584), 2002
Chaotic signals, signals generated by a nonlinear dynamical system in chaotic state, may be useful models for many natural phenomena. In this paper we show a family of first-order difference equations with autocorrelation function identical to first-order autoregressive processes AR(1).
D. Luengo, C. Pantaleon, I. Santamaria
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Univariate AR(1) Models

1996
This chapter is devoted to the mathematical analysis of learning to become rational in the simplest purely dynamic case. More precisely, we consider a model in which the univariate endogenous variable depends only on its one period lagged value, the predictions of agents, and a disturbance term.
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AR(1) model with skew-normal innovations

Metrika, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sharafi, M., Nematollahi, A. R.
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Asymptotic Expansions Associated with the AR(1) Model with Unknown Mean

Econometrica, 1983
In this paper we attempt to extend directly the results of \textit{P. C. B. Phillips} [ibid. 45, 463-485 (1977; Zbl 0349.62070)] so that we only deal with the AR(1) model with unknown, constant mean. This enables us to obtain the explicit expressions for asymptotic expansions.
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A Modification of the Edgeworth Approximation in the AR (1) Model

Biometrical Journal, 1992
AbstractThis paper considers the sampling distribution problem of the least squares estimator for the parameter of some special autoregressive models. The Edgeworth approximation has been derived and a modification is proposed to improve its accuracy.
Shu‐Ing Liu, Chien‐Chou Su, Shu‐Ing Liu Chien‐Chou   +2 more
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Adaptive Forecasting with an AR(1) Model

1977
Abstract : Updating formulas for the forecasts of a one-parameter autoregressive model are obtained when the parameter is assumed random. It is shown that the updated forecasts are similar to those derived from exponentially weighted moving average forecasts with the important difference that forecasts can lie outside the interval containing the old ...
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On nonparametric estimation in nonlinear AR(1)-models

Statistics & Probability Letters, 1999
This paper considers the estimation problem of the mean function and the conditional variance (the volatility function) of a nonlinear first-order autoregressive model nonparametrically. Minimax rates of convergence are established over a scale of Besov bodies \({\mathcal B}_{spq}\) and a range of global \(L_{p'}\) error measurements, for \(1\leq p ...
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Stochastic resonance in discrete time nonlinear AR(1) models

IEEE Transactions on Signal Processing, 1999
This paper deals with stochastic resonance. This nonlinear physical phenomenon generally occurs in bistable systems excited by random input noise plus a sinusoid. Through its internal dynamics, such a system forces cooperation between the input noise and the input sine: provided the existence of fine tuning between the power noise and the dynamics, the
Zozor, Steeve, Amblard, Pierre-Olivier
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