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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… Expand
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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… Expand
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Highly Cited
2017
Highly Cited
2017
The framework of normalizing flows provides a general strategy for flexible variational inference of posteriors over latent… Expand
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Highly Cited
2016
Highly Cited
2016
Thank you very much for downloading likelihood based inference in cointegrated vector autoregressive models. Maybe you have… Expand
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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… Expand
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Highly Cited
1999
Highly Cited
1999
This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model… Expand
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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… Expand
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Highly Cited
1992
Highly Cited
1992
Abstract We present a multiresolution simultaneous autoregressive (MR-SAR) model for texture classification and segmentation… Expand
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Highly Cited
1991
Highly Cited
1991
This paper contains the likelihood analysis of vector autoregressive models allowing for cointegration. The author derives the… Expand
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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… Expand
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Highly Cited
1970
Highly Cited
1970
Many statistical models, and in particular autoregressive-moving average time series models, can be regarded as means of… Expand
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