AbstractIn this note some problems of asymptotic inference in a class of non-stationary stochastic processes are considered. In particular, it is shown that no criterion based on the existence of uniformly most powerful tests over a local neighborhood can be used in this situation
AbstractA Galton-Watson branching tree is sampled, yielding a derived vector process of family sizes...
This thesis is primarily concerned with the investigation of asymptotic properties of the maximum l...
AbstractIn this paper, a new asymptotic theory is developed for nearly nonstationary autoregressive ...
In this note some problems of asymptotic inference in a class of non-stationary stochastic processes...
AbstractIn this note some problems of asymptotic inference in a class of non-stationary stochastic p...
AbstractThis paper develops an approach to conditional inference for nonergodic stochastic process m...
AbstractThis is a survey of some aspects of large-sample inference for stochastic processes. A unifi...
The study of locally stationary processes contains theory and methods about a class of processes tha...
This is a survey of some aspects of large-sample inference for stochastic processes. A unified frame...
AbstractWe give two local asymptotic minimax bounds for models which admit a local quadratic approxi...
Summary. We give an overview of recent developments in the theory of statistical inference for stoch...
AbstractThis paper is concerned with the problem of finding a suitable (asymptotic) efficiency crite...
The problem of demonstrating the limiting normality of posterior distributions arising from stochast...
In certain cases statistical methods based on standard maximum likelihood asymptotics become valid a...
AbstractThe local asymptotic normality (LAN) of the log-likelihood ratio for a class of Markovian no...
AbstractA Galton-Watson branching tree is sampled, yielding a derived vector process of family sizes...
This thesis is primarily concerned with the investigation of asymptotic properties of the maximum l...
AbstractIn this paper, a new asymptotic theory is developed for nearly nonstationary autoregressive ...
In this note some problems of asymptotic inference in a class of non-stationary stochastic processes...
AbstractIn this note some problems of asymptotic inference in a class of non-stationary stochastic p...
AbstractThis paper develops an approach to conditional inference for nonergodic stochastic process m...
AbstractThis is a survey of some aspects of large-sample inference for stochastic processes. A unifi...
The study of locally stationary processes contains theory and methods about a class of processes tha...
This is a survey of some aspects of large-sample inference for stochastic processes. A unified frame...
AbstractWe give two local asymptotic minimax bounds for models which admit a local quadratic approxi...
Summary. We give an overview of recent developments in the theory of statistical inference for stoch...
AbstractThis paper is concerned with the problem of finding a suitable (asymptotic) efficiency crite...
The problem of demonstrating the limiting normality of posterior distributions arising from stochast...
In certain cases statistical methods based on standard maximum likelihood asymptotics become valid a...
AbstractThe local asymptotic normality (LAN) of the log-likelihood ratio for a class of Markovian no...
AbstractA Galton-Watson branching tree is sampled, yielding a derived vector process of family sizes...
This thesis is primarily concerned with the investigation of asymptotic properties of the maximum l...
AbstractIn this paper, a new asymptotic theory is developed for nearly nonstationary autoregressive ...
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