Titlebook: Asymptotic Expansions for General Statistical Models; Johann Pfanzagl Book 1985 Springer-Verlag Berlin Heidelberg 1985 approximation.behav

Obsolescent

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書目名稱Asymptotic Expansions for General Statistical Models讀者反饋




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Explicate

恩惠

A Logic-Based Calculus of Eventsluate the concentration of its distribution, P*K, about κ(P). In the following sections we provide the conceptual framework for this task. In Section 7.2 we introduce the concept of a randomized estimator.

TATE

Joachim W. Schmidt,Constantino Thanose quality of such confidence procedures, defined in terms of covering probabilities, can be equivalently expressed by the concentration of the confidence bound. Results on the concentration of confidence bounds can be applied in particular to the concentration of estimators.

拍翅

Lecture Notes in Statisticshttp://image.papertrans.cn/b/image/163801.jpg

圖畫文字

Asymptotic Expansions for Power Functions,tic log(.) are most powerful for . against .. In this section it will be shown that sequences of test statistics log(.), n ∈ ?, are most powerful of order o(n.) under relatively weak conditions on the remainder sequence R., n ∈ ?.

貞潔

Evaluating the Performance of Estimators,luate the concentration of its distribution, P*K, about κ(P). In the following sections we provide the conceptual framework for this task. In Section 7.2 we introduce the concept of a randomized estimator.

mighty

Asymptotic Bounds for the Performance of Confidence Procedures and Estimators,e quality of such confidence procedures, defined in terms of covering probabilities, can be equivalently expressed by the concentration of the confidence bound. Results on the concentration of confidence bounds can be applied in particular to the concentration of estimators.

朦朧

https://doi.org/10.1007/978-3-319-97943-4Let β be a family of mutually absolutely continuous p-measures. We fix a dominating measure μ, and use the small letter p to denote the μ-density of P ∈ β.

仲裁者

https://doi.org/10.1007/978-3-319-97943-4The concept of a differentiable path is motivated by the aspiration to describe the local structure of a given family of p-measures. Our purpose is to grasp those local properties which are relevant for the asymptotic performance of statistical procedures.