This paper develops an asymptotic theory for R-estimation based on a square-integrable, not necessarily bounded, score function in the pth order stationary autoregressive model. Asymptotic uniform linearity of a class of linear rank statistics is established and the asymptotic normality of the corresponding R-estimators is derived. This paper thus solves a long-standing problem in the development of the asymptotics for rank estimators under the autoregressive setup. The proofs use a combination of the approximation technique, the contiguity technique and the weak convergence technique of Hájek, Jureková and Koul, respectively
This paper proves strong consistency, along with a rate, of a class of generalized M-estimators for ...
In this paper, we extend the classical idea of Rank estimation of parameters from homoscedastic prob...
Absolutely regular processes, Autoregressive time series, Geometric absolute regularity, GR-estimate...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
In this paper, we extend the classical idea of Rank-estimation of parameters from homoscedastic prob...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
The thesis deals with R-estimators, estimators based on ranks. They were originally proposed by Hodg...
This paper extends the concept of regression and autoregression quantiles and rank scores to a very ...
This paper establishes an asymptotic representation for regression and autoregression rank score sta...
International audienceThe purpose of this paper is to prove, under mild conditions, the asymptotic n...
International audienceThe purpose of this paper is to prove, under mild conditions, the asymptotic n...
International audienceThe purpose of this paper is to prove, under mild conditions, the asymptotic n...
International audienceThe purpose of this paper is to prove, under mild conditions, the asymptotic n...
We establish asymptotic normality and consistency for rank-based estimators of autoregressive-moving...
This paper proves strong consistency, along with a rate, of a class of generalized M-estimators for ...
In this paper, we extend the classical idea of Rank estimation of parameters from homoscedastic prob...
Absolutely regular processes, Autoregressive time series, Geometric absolute regularity, GR-estimate...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
In this paper, we extend the classical idea of Rank-estimation of parameters from homoscedastic prob...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The ...
The thesis deals with R-estimators, estimators based on ranks. They were originally proposed by Hodg...
This paper extends the concept of regression and autoregression quantiles and rank scores to a very ...
This paper establishes an asymptotic representation for regression and autoregression rank score sta...
International audienceThe purpose of this paper is to prove, under mild conditions, the asymptotic n...
International audienceThe purpose of this paper is to prove, under mild conditions, the asymptotic n...
International audienceThe purpose of this paper is to prove, under mild conditions, the asymptotic n...
International audienceThe purpose of this paper is to prove, under mild conditions, the asymptotic n...
We establish asymptotic normality and consistency for rank-based estimators of autoregressive-moving...
This paper proves strong consistency, along with a rate, of a class of generalized M-estimators for ...
In this paper, we extend the classical idea of Rank estimation of parameters from homoscedastic prob...
Absolutely regular processes, Autoregressive time series, Geometric absolute regularity, GR-estimate...