Add to ORKG<正> In this paper a recursive method is given for estimating model under the natural conditions that the best linear predictor is the best predictor (in the mean square sense).Under these conditions we can prove the estimators of p_0 and q_o are strongly consistent.The asymptotic normality and the l...02169-19
Autoregressive moving average (ARMA) models are a fundamental tool in timeseries analysis that offer...
Autoregressive moving average (ARMA) models are a funda-mental tool in time series analysis that off...
An algorithm for robust fitting of AR models is given, based on a linear regression idea. The new me...
A recursive algorithm for ARMA (autoregressive moving average) filtering has been developed in a com...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
This study is based on the observation that if the bootstrapping is combined with different paramete...
Recursive estimation methods for time series models usually make use of recurrences for the vector o...
The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem ...
The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem ...
The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem ...
The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem ...
The present paper aims to present an entirely new approach for the development of "exact" recursive ...
This paper gives an expression for the minimum mean squared error predictor of the single equation A...
The paper deals with recursive robust estimation of the autoregressive models with additive outliers...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
Autoregressive moving average (ARMA) models are a fundamental tool in timeseries analysis that offer...
Autoregressive moving average (ARMA) models are a funda-mental tool in time series analysis that off...
An algorithm for robust fitting of AR models is given, based on a linear regression idea. The new me...
A recursive algorithm for ARMA (autoregressive moving average) filtering has been developed in a com...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
This study is based on the observation that if the bootstrapping is combined with different paramete...
Recursive estimation methods for time series models usually make use of recurrences for the vector o...
The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem ...
The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem ...
The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem ...
The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem ...
The present paper aims to present an entirely new approach for the development of "exact" recursive ...
This paper gives an expression for the minimum mean squared error predictor of the single equation A...
The paper deals with recursive robust estimation of the autoregressive models with additive outliers...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
Autoregressive moving average (ARMA) models are a fundamental tool in timeseries analysis that offer...
Autoregressive moving average (ARMA) models are a funda-mental tool in time series analysis that off...
An algorithm for robust fitting of AR models is given, based on a linear regression idea. The new me...