Add to ORKGThis paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent (see Kim, Qian and Schmidt (1999)), using high-order moments can provide substantial efficiency gains for estimating the AR(p) model when the noise is only uncorrelated.autoregressive process, efficiency gains, GMM, empirical autocorrelations, Yule-Walker estimator.
This paper considers the problem of estimating the parameters of an autoregressive (AR) process in p...
This paper considers the problem of estimating the parameters of an autoregressive (AR) process in p...
This paper considers the problem of estimating the parameters of an autoregressive (AR) process in p...
This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the c...
none3This paper deals with the problem of identifying autoregressive models in presence of additive ...
A common approach in modeling signals in many engineering applications consists in adopting autoregr...
A common approach in modeling signals in many engineering applications consists in adopting autoregr...
This paper deals with the problem of identifying autoregressive models in presence of additive measu...
The problem of estimating the parameters of a non-Gaussian autoregressive process is addressed. Depa...
The problem of estimating the parameters of a non-Gaussian autoregressive process is addressed. Depa...
This paper deals with the problem of identifying autoregressive models in presence of additive measu...
none3A common approach in modeling signals in many engineering applications consists in adopting aut...
The problem of estimating the parameters of a non-Gaussian autoregressive process is addressed. Depa...
We consider regularly sampled processes that have most of their spectral power at low frequencies. A...
We consider regularly sampled processes that have most of their spectral power at low frequencies. A...
This paper considers the problem of estimating the parameters of an autoregressive (AR) process in p...
This paper considers the problem of estimating the parameters of an autoregressive (AR) process in p...
This paper considers the problem of estimating the parameters of an autoregressive (AR) process in p...
This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the c...
none3This paper deals with the problem of identifying autoregressive models in presence of additive ...
A common approach in modeling signals in many engineering applications consists in adopting autoregr...
A common approach in modeling signals in many engineering applications consists in adopting autoregr...
This paper deals with the problem of identifying autoregressive models in presence of additive measu...
The problem of estimating the parameters of a non-Gaussian autoregressive process is addressed. Depa...
The problem of estimating the parameters of a non-Gaussian autoregressive process is addressed. Depa...
This paper deals with the problem of identifying autoregressive models in presence of additive measu...
none3A common approach in modeling signals in many engineering applications consists in adopting aut...
The problem of estimating the parameters of a non-Gaussian autoregressive process is addressed. Depa...
We consider regularly sampled processes that have most of their spectral power at low frequencies. A...
We consider regularly sampled processes that have most of their spectral power at low frequencies. A...
This paper considers the problem of estimating the parameters of an autoregressive (AR) process in p...
This paper considers the problem of estimating the parameters of an autoregressive (AR) process in p...
This paper considers the problem of estimating the parameters of an autoregressive (AR) process in p...