Results 231 to 240 of about 766,459 (260)

The jackknife and regression with AR(1) errors

Economics Letters, 1988
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Kwok, Ben, Veall, Michael R.
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Chaotic AR(1) model estimation

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
Chaotic signals generated by iterating nonlinear difference equations may be useful models for many natural phenomena. We propose a family of chaotic models for signal processing applications. The chaotic signals generated by this family of first-order difference equations have autocorrelations identical to stochastic first-order autoregressive (AR ...
Carlos Pantaleón, David Luengo, Ignacio Santamaría   +2 more
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THE STABILITY OF THE AR(1) PROCESS WITH AN AR(1) COEFFICIENT

Journal of Time Series Analysis, 1985
Abstract. In this paper we consider a simple time varying coefficient ARMA process:the AR (1) process with an AR (1) coefficient. A basic requirement of the process is that the output has finite variance, and we derive a condition on the parameters for this to be satisfied.
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Exact predictors for a generalized ar(1) process with an ar(1) parameter

Communications in Statistics - Theory and Methods, 1988
The generalized AR(1) process y t = a t y t-1+ v t is considered, where the parameter a t follows the AR(1) process a t = Ga t-1+ w t.Assuming that V t and w t are Gaussian and independent, the first six exact predictors for future values of y t are derived. These exact predictors are compared with Box-Jenkins -type approximations.
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STRUCTURAL CHANGE IN AR(1) MODELS

Econometric Theory, 2001
This paper investigates the consistency of the least squares estimators and derives their limiting distributions in an AR(1) model with a single structural break of unknown timing. Let β1 and β2 be the preshift and postshift AR parameter, respectively. Three cases are considered: (i) |β1| < 1 and |β2| < 1; (ii) |β1| < 1 and β2 = 1; and
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The polynomial aggregated AR(1) model*

The Econometrics Journal, 2006
Summary: This paper develops a new kind of aggregation model. We extend the work of \textit{M. Linden} [Econ. Lett. 64, No.~1, 31--36 ( (1999; Zbl 1049.62510) to allow the AR coefficient to be drawn from a polynomial density function. The polynomial density incorporates a wealth of multi-modal density functions as special cases.
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A threshold AR(1) model

Journal of Applied Probability, 1984
We consider the model where φ 1, φ 2 are real coefficients, not necessarily equal, and the at ,'s are a sequence of i.i.d. random variables with mean 0. Necessary and sufficient conditions on the φ 's are given for stationarity of the process.
Petruccelli, Joseph D., Woolford, Samuel W.   +1 more
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On unequally spaced AR(1) process

Kybernetika, 2003
Summary: A discrete autoregressive process of first order is considered. The process is observed at unequally spaced time instants. Both the least squares estimate and the maximum likelihood estimate of the autocorrelation coefficient are analyzed.
Jan Sindelár, Jirí Knízek
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CONFIDENCE REGIONS FOR PARAMETERS IN THE AR(1) MODEL

Journal of Time Series Analysis, 1995
Abstract.The construction of approximate joint and marginal confidence regions for parameters in the first‐order autoregressive time series model is discussed. These regions are based on the large sample distributions of the likelihood ratio (and approximations to it), of the maximum likelihood estimates and of the score statistics.
Hamilton, David C., Wu, Ka Ho
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