This diploma thesis dissertate about consistency and asymptotic representation of the least weighted squares estimator (LWS). In preface we mention reasons for data processing with robust statistical methods and differencies between LWS estimator and other methods (the least squares estimator, the least trimmed squares estimator). In the following sections we show proofs of lemmas about consistency and assymptotic representation of the least weighted squares estimator. Compared to the similar results published before we have concluded ours based on different conditions. Impulse for this thesis were new results about uniform convergence of empirical function mentioned in work from prof. Jan Ámos Víšek - Kolmogorov-Smirnov statistics in multi...
Abstract. We analyze the asymptotic properties of estimators based on optimizing an extended least s...
A vector autoregression with deterministic terms and with no restrictions to its characteristic root...
summary:Asymptotic normality of the least trimmed squares estimator is proved under general conditio...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
The consistency and the asymptotic normality of the least weighted squares is proved and its asympto...
summary:The present paper deals with least weighted squares estimator which is a robust estimator an...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
We consider the consistency and weak convergence of $S$-estimators in the linear regression model. S...
AbstractThe paper uses empirical process techniques to study the asymptotics of the least-squares es...
A vector autoregression with deterministic terms with no restrictions to its characteristic roots is...
The paper uses empirical process techniques to study the asymptotics of the least-squares estimator ...
The paper uses empirical process techniques to study the asymptotics of the least-squares estimator ...
Thesis (Ph.D.)--University of Washington, 2018We revisit and make progress on some old but challengi...
We consider a heteroscedastic linear regression model with replication. To estimate the variances, o...
A vector autoregression with deterministic terms and with no restrictions to its characteristic root...
Abstract. We analyze the asymptotic properties of estimators based on optimizing an extended least s...
A vector autoregression with deterministic terms and with no restrictions to its characteristic root...
summary:Asymptotic normality of the least trimmed squares estimator is proved under general conditio...
This diploma thesis dissertate about consistency and asymptotic representation of the least weighted...
The consistency and the asymptotic normality of the least weighted squares is proved and its asympto...
summary:The present paper deals with least weighted squares estimator which is a robust estimator an...
summary:The consistency of the least trimmed squares estimator (see Rousseeuw [Rous] or Hampel et al...
We consider the consistency and weak convergence of $S$-estimators in the linear regression model. S...
AbstractThe paper uses empirical process techniques to study the asymptotics of the least-squares es...
A vector autoregression with deterministic terms with no restrictions to its characteristic roots is...
The paper uses empirical process techniques to study the asymptotics of the least-squares estimator ...
The paper uses empirical process techniques to study the asymptotics of the least-squares estimator ...
Thesis (Ph.D.)--University of Washington, 2018We revisit and make progress on some old but challengi...
We consider a heteroscedastic linear regression model with replication. To estimate the variances, o...
A vector autoregression with deterministic terms and with no restrictions to its characteristic root...
Abstract. We analyze the asymptotic properties of estimators based on optimizing an extended least s...
A vector autoregression with deterministic terms and with no restrictions to its characteristic root...
summary:Asymptotic normality of the least trimmed squares estimator is proved under general conditio...