In order to obtain many of the classical results in the theory of statistical estimation, it is usual to impose regularity conditions on the distributions under consideration. In small sample and large sample theories of estimation there are well established sets of regularity conditions, and it is worth while to examine what may follow if any one of these regularity conditions fail to hold. "Non-regular estimation" literally means the theory of statistical estimation when some or other of the regularity conditions fail to hold. In this monograph, the authors present a systematic study of the...
In order to obtain many of the classical results in the theory of statistical estimation, it is usual to impose regularity conditions on the distribut...
This monograph is a collection of results recently obtained by the authors. Most of these have been published, while others are awaitlng publication. Our investigation has two main purposes. Firstly, we discuss higher order asymptotic efficiency of estimators in regular situa tions. In these situations it is known that the maximum likelihood estimator (MLE) is asymptotically efficient in some (not always specified) sense. However, there exists here a whole class of asymptotically efficient estimators which are thus asymptotically equivalent to the MLE. It is required to make finer...
This monograph is a collection of results recently obtained by the authors. Most of these have been published, while others are awaitlng publication. ...
Masafumi Akahira and Kei Takeuchi have collaborated in research on mathematical statistics for nearly 30 years. This volume is a collection of their papers, covering the theory of estimation, such as asymptotic, non-regular, and sequential.
Masafumi Akahira and Kei Takeuchi have collaborated in research on mathematical statistics for nearly 30 years. This volume is a collection of their p...
