Add to ORKGIn this short note I apply the methodology of game-theoretic probability to calculating non-asymptotic confidence intervals for the coefficient of a simple first order scalar autoregressive model. The most distinctive feature of the proposed procedure is that with high probability it produces confidence intervals that always cover the true parameter value when applied sequentially
The purpose of this paper is to receive a second order expansion of the t-statistic in AR(1) model i...
A new method is proposed for constructing confidence intervals in autoregressive models with linear ...
We develop a method for constructing confidence regions on the mean vectors of multivariate processe...
In this short note I apply the methodology of game-theoretic probability to calculating non-asymptot...
The purpose of this paper is to provide theoretical justification for some existing methods for cons...
Often we are interested in the largest root of an autoregressive process. Available methods rely on ...
The paper considers the estimation problem of the autoregressive parameter in th
In this paper, we propose a new method for constructing confidence intervals for the autoregressive ...
This paper considers estimation and inference concerning the autoregressive coefficient () in a pane...
The purpose of this paper is to differentiate between several asymptotically valid methods for confi...
When the variance is unknown, the problem of setting fixed width confidence intervals for the mean m...
This paper proposes a GMM-based method for asymptotic confidence interval construction in stationary...
Sequential methods were used to solve testing problems more efficiently. But at the same time, they ...
This paper considers estimation and inference concerning the autoregressive coefficient ( ρ ) in a p...
The article considers the problem of estimating linear parameters in stochastic regression models wi...
The purpose of this paper is to receive a second order expansion of the t-statistic in AR(1) model i...
A new method is proposed for constructing confidence intervals in autoregressive models with linear ...
We develop a method for constructing confidence regions on the mean vectors of multivariate processe...
In this short note I apply the methodology of game-theoretic probability to calculating non-asymptot...
The purpose of this paper is to provide theoretical justification for some existing methods for cons...
Often we are interested in the largest root of an autoregressive process. Available methods rely on ...
The paper considers the estimation problem of the autoregressive parameter in th
In this paper, we propose a new method for constructing confidence intervals for the autoregressive ...
This paper considers estimation and inference concerning the autoregressive coefficient () in a pane...
The purpose of this paper is to differentiate between several asymptotically valid methods for confi...
When the variance is unknown, the problem of setting fixed width confidence intervals for the mean m...
This paper proposes a GMM-based method for asymptotic confidence interval construction in stationary...
Sequential methods were used to solve testing problems more efficiently. But at the same time, they ...
This paper considers estimation and inference concerning the autoregressive coefficient ( ρ ) in a p...
The article considers the problem of estimating linear parameters in stochastic regression models wi...
The purpose of this paper is to receive a second order expansion of the t-statistic in AR(1) model i...
A new method is proposed for constructing confidence intervals in autoregressive models with linear ...
We develop a method for constructing confidence regions on the mean vectors of multivariate processe...