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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… 
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Papers overview

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Highly Cited
2019
Highly Cited
2019
With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better… 
Highly Cited
2011
Highly Cited
2011
Radiocarbon dating is routinely used in paleoecology to build chronolo- gies of lake and peat sediments, aiming at inferring a… 
Highly Cited
2005
Highly Cited
2005
Autoregressive stochastic models for the computer simulation of correlated Rayleigh fading processes are investigated. The… 
Highly Cited
2002
Highly Cited
2002
Recognition and analysis of spatial autocorrelation has defined a new par- adigm in ecology. Attention to spatial pattern can… 
Review
2000
Review
2000
This paper surveys recent developments related to the smooth transition autoregressive (STAR) time series model and several of… 
Highly Cited
1998
Highly Cited
1998
This paper proposes a new statistical model for the analysis of data which arrive at irregular intervals. The model treats the… 
Review
1995
Review
1995
Introduction Econometric analysis of long-run relations has been the focus of much theoretical and empirical research in… 
Highly Cited
1991
Highly Cited
1991
This paper contains the likelihood analysis of vector autoregressive models allowing for cointegration. The author derives the… 
Highly Cited
1979
Highly Cited
1979
Abstract Let n observations Y 1, Y 2, ···, Y n be generated by the model Y t = pY t−1 + e t , where Y 0 is a fixed constant and… 
Highly Cited
1970
Highly Cited
1970
Many statistical models, and in particular autoregressive-moving average time series models, can be regarded as means of…