The target of this paper is to discuss the existent difference of Asymptotic Theory in Statistics comparing to Mathematics. There is a need for a limiting distribution in Statistics, usually the Normal one. Adopting the sequential principle the first-order autoregression model and the stochastic approximation are referred for their particular interest for asymptotic results.info:eu-repo/semantics/publishedVersio
Stochastic approximations is a rich branch of probability theory and has a wide range of application...
The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin–Wa...
The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin–Wa...
This brief note summarizes some important results in asymptotic theory in probability. The main moti...
This book is devoted to a systematic analysis of asymptotic behavior of distributions of various typ...
This thesis deals with two topics in asymptotic statistics. A concept of asymptotic optimality for s...
This thesis deals with two topics in asymptotic statistics. A concept of asymptotic optimality for s...
Asymptotic approaches are widely used in statistics. Generally, I recognize two applications of asym...
This book contains articles arising from a conference in honour of mathematician-statistician Miklόs...
In certain cases statistical methods based on standard maximum likelihood asymptotics become valid a...
Providing a broad toolkit of analytical methods, this book shows how asymptotics, when coupled with ...
The asymptotic theory of estimators obtained from estimating functions is re-viewed and some new res...
AbstractI discuss five topics of current interest in asymptotic analysis: the use of probabilistic m...
The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin–Wa...
Stochastic approximations is a rich branch of probability theory and has a wide range of application...
Stochastic approximations is a rich branch of probability theory and has a wide range of application...
The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin–Wa...
The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin–Wa...
This brief note summarizes some important results in asymptotic theory in probability. The main moti...
This book is devoted to a systematic analysis of asymptotic behavior of distributions of various typ...
This thesis deals with two topics in asymptotic statistics. A concept of asymptotic optimality for s...
This thesis deals with two topics in asymptotic statistics. A concept of asymptotic optimality for s...
Asymptotic approaches are widely used in statistics. Generally, I recognize two applications of asym...
This book contains articles arising from a conference in honour of mathematician-statistician Miklόs...
In certain cases statistical methods based on standard maximum likelihood asymptotics become valid a...
Providing a broad toolkit of analytical methods, this book shows how asymptotics, when coupled with ...
The asymptotic theory of estimators obtained from estimating functions is re-viewed and some new res...
AbstractI discuss five topics of current interest in asymptotic analysis: the use of probabilistic m...
The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin–Wa...
Stochastic approximations is a rich branch of probability theory and has a wide range of application...
Stochastic approximations is a rich branch of probability theory and has a wide range of application...
The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin–Wa...
The purpose of this paper is to provide a sharp analysis on the asymptotic behavior of the Durbin–Wa...