Add to ORKGThis paper compares the first-order bias approximation for the autoregressive (AR) coefficients in stable AR models in the presence of deterministic terms. It is shown that the bias due to inclusion of an intercept and trend is twice as large as the bias due to an intercept. For the AR(1) model, the accuracy of this approximation is investigated by simulation
The purpose of this paper is to differentiate between several asymptotically valid methods for confi...
This paper investigates Threshold Autoregressive (TAR) models that contain a limited number of obser...
An approximation to order T-² is obtained for the bias of the full vector of least- squares estimate...
This paper derives the Bartlett factors that can be used to obtain higher-order improvements for tes...
We analyze the properties of various methods for bias-correcting parameter estimates in both station...
The Bartlett correction is derived for testing hypotheses about the autoregressive parameter ρ in th...
This paper compares the behaviour of a bias-corrected estimator assuming strongly exogenous regresso...
Bartlett corrections are derived for testing hypotheses about the autoregressive parameter ρ in the ...
Although weights of some system poles of the AR model are asymptotically constant for model order ch...
A symbolic method which can be used to obtain the asymptotic bias and variance coefficients to order...
In this paper we work with multivariate time series that follow a Dynamic Factor Model. In particula...
The asymptotic bias to terms of order $T\sp{-1}$, where $T$ is the observed series length, is studie...
Most of the existing autoregressive models presume that the observations are perfectly measured. In ...
The Yule-Walker (YW) method for autoregressive (AR) estimation uses lagged-product (LP) autocorrelat...
AbstractFor a first-order autoregressive AR(1) model with zero initial value, xt = αxt−1 + εt, we pr...
The purpose of this paper is to differentiate between several asymptotically valid methods for confi...
This paper investigates Threshold Autoregressive (TAR) models that contain a limited number of obser...
An approximation to order T-² is obtained for the bias of the full vector of least- squares estimate...
This paper derives the Bartlett factors that can be used to obtain higher-order improvements for tes...
We analyze the properties of various methods for bias-correcting parameter estimates in both station...
The Bartlett correction is derived for testing hypotheses about the autoregressive parameter ρ in th...
This paper compares the behaviour of a bias-corrected estimator assuming strongly exogenous regresso...
Bartlett corrections are derived for testing hypotheses about the autoregressive parameter ρ in the ...
Although weights of some system poles of the AR model are asymptotically constant for model order ch...
A symbolic method which can be used to obtain the asymptotic bias and variance coefficients to order...
In this paper we work with multivariate time series that follow a Dynamic Factor Model. In particula...
The asymptotic bias to terms of order $T\sp{-1}$, where $T$ is the observed series length, is studie...
Most of the existing autoregressive models presume that the observations are perfectly measured. In ...
The Yule-Walker (YW) method for autoregressive (AR) estimation uses lagged-product (LP) autocorrelat...
AbstractFor a first-order autoregressive AR(1) model with zero initial value, xt = αxt−1 + εt, we pr...
The purpose of this paper is to differentiate between several asymptotically valid methods for confi...
This paper investigates Threshold Autoregressive (TAR) models that contain a limited number of obser...
An approximation to order T-² is obtained for the bias of the full vector of least- squares estimate...