Add to ORKGThe purpose of this paper is to use Bahadur’s asymptotic relative efficiency measure to compare the performance of various tests of autoregressive (AR) versus moving average (MA) error processes in regression models. Tests to be examined include non-nested procedures of the models against each other, and classical procedures based upon testing both the AR and MA error processes against the more general autoregressive-moving average model
Deciding the order of differencing is an important part in the specification of an autoregressive in...
A new class of time series models known as Generalized Autoregressive of order one with first-order ...
The threshold autoregressive moving average models, symbolized as TARMA, is nonlinear class of time ...
This paper considers testing for MA(1) against AR(1) disturbances in the linear regression model. Te...
We compare the performance of the inverse and ordinary (partial) autocorrelations for time series mo...
In this paper, we generalise the partly linear autoregression model considered in the literature by ...
Abstract: In this paper we will consider a linear regression model with the sequence of error terms ...
In this paper we will consider a linear regression model with the sequence of error terms following ...
This paper is concerned with the problem of testing the hypothesis that the disturbances of a regres...
Robust analogues of the Wald and the Rao score statistics are presented for testing composite hypoth...
A direct application of autoregressive (AR) models with independent and identically distributed (iid...
The most important assumption about time series and econometrics data is stationarity. Therefore, th...
Includes bibliographical references (pages [52]-53)This study designs an exponentially weighted movi...
The efficiency of estimation procedures and the validity of testing procedures in simple and multipl...
A problem of interest in economic and finance applications is testing whether ARMA (Autoregressive m...
Deciding the order of differencing is an important part in the specification of an autoregressive in...
A new class of time series models known as Generalized Autoregressive of order one with first-order ...
The threshold autoregressive moving average models, symbolized as TARMA, is nonlinear class of time ...
This paper considers testing for MA(1) against AR(1) disturbances in the linear regression model. Te...
We compare the performance of the inverse and ordinary (partial) autocorrelations for time series mo...
In this paper, we generalise the partly linear autoregression model considered in the literature by ...
Abstract: In this paper we will consider a linear regression model with the sequence of error terms ...
In this paper we will consider a linear regression model with the sequence of error terms following ...
This paper is concerned with the problem of testing the hypothesis that the disturbances of a regres...
Robust analogues of the Wald and the Rao score statistics are presented for testing composite hypoth...
A direct application of autoregressive (AR) models with independent and identically distributed (iid...
The most important assumption about time series and econometrics data is stationarity. Therefore, th...
Includes bibliographical references (pages [52]-53)This study designs an exponentially weighted movi...
The efficiency of estimation procedures and the validity of testing procedures in simple and multipl...
A problem of interest in economic and finance applications is testing whether ARMA (Autoregressive m...
Deciding the order of differencing is an important part in the specification of an autoregressive in...
A new class of time series models known as Generalized Autoregressive of order one with first-order ...
The threshold autoregressive moving average models, symbolized as TARMA, is nonlinear class of time ...