Autoregressive model

Known as: Autoregressive, AR process, Stochastic term 
In statistics and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it describes certain time… (More)
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Topic mentions per year

Topic mentions per year

1951-2018
0500100019512017

Papers overview

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Highly Cited
2010
Highly Cited
2010
This paper proposes a new method for identification of time-varying autoregressive (TVAR) models based on local polynomial… (More)
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Highly Cited
2008
Highly Cited
2008
The challenge of image interpolation is to preserve spatial details. We propose a soft-decision interpolation technique that… (More)
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Highly Cited
2007
Highly Cited
2007
JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of… (More)
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Highly Cited
2007
Highly Cited
2007
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org… (More)
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Highly Cited
2007
Highly Cited
2007
Aim Spatial autocorrelation is a frequent phenomenon in ecological data and can affect estimates of model coefficients and… (More)
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Highly Cited
2002
Highly Cited
2002
Recognition and analysis of spatial autocorrelation has defined a new paradigm in ecology. Attention to spatial pattern can lead… (More)
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Highly Cited
2001
Highly Cited
2001
Autoregressive stochastic models for the computer simulation of correlated Rayleigh fading processes are investigated. The… (More)
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Highly Cited
1999
Highly Cited
1999
The assumption of Gaussian innovation terms in linear time series analysis is quite restrictive. Under this assumption, both the… (More)
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Highly Cited
1997
Highly Cited
1997
This paper examines the use of autoregressive distributed lag (ARDL) models for the analysis of long-run relations when the… (More)
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Highly Cited
1986
Highly Cited
1986
A natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in Engle (1982) to allow for… (More)
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