Questions tagged [admissibility]
Admissible estimator: there is no other estimator for which the risk is $\leq$ for all possible true values of the target parameter.
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General Strategy to show an estimator is admissible?
I am getting into decision theory and I was wondering if there was a general way to check if a an estimator is admissible.
(PS This question might have already been asked, sorry if that is the case I ...
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Comparing Risk of Estimators with unknown parameter
I would like to compare the risk of 2 estimators.
Let $X_1,..,X_n$ are $\mathcal{N}(\theta,1)$. I have to show that the average $\frac{1}{n}\sum X_i$ is not admissible if we have prior knowledge that $...
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Is the admissible minimax decision rule ever a randomized action in frequentist statistics?
Are randomized action as opposed to pure action ever an admissible minimax rule in frequentist statistics,
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Admissible Empirical Bayes Examples
I would like to hear about a few simple empirical bayes estimators that are admissible for high (i.e. at least 3) dimensional parameter space.
What are some textbook lollipop examples to study for ...
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Inadmissible MLE
Let us say, I have a distribution with some unknown parameter and I find the MLE of the parameter. I prove that the MLE is inadmissible using some other estimator. Why is this not in a contradiction ...
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Empirical Bayes (In)Admissibility
Sticking to a pure Bayesian approach to statistics with proper priors most of the time leads to admissible estimators.
Nevertheless there is good reason to use Empirical Bayes in many cases, and the ...
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Admissible Bayes Rule
In the following wikipedia entry
https://en.wikipedia.org/wiki/Admissible_decision_rule
it is written that
"Bayes rules with respect to proper priors are virtually always admissible"
What do they ...
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Is an inadmissible estimator necessarily dominated by some admissible estimator
Basic example: $X$ has a $p$-variate iid standard Normal distribution; the sample mean is not admissible if $p>2$ and is dominated by the Stein shrinkage estimator.
However, the Stein shrinkage ...
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Model with admissible estimator(s) that are not the Bayes estimator for any choice of prior?
Every Bayes estimator is admissible, to the best of my knowledge. (Related questions - 1,2.) I recall my professor mentioning once during a lecture that, at least as rough intuition, the converse is ...
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How to choose loss function (in unbounded parameter space)?
How does one choose a loss function for a given problem? (I've looked through stackexchange, and I haven't been able to find a thread that discusses this.)
Let say I observe some data $x \in \mathbb{...
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Well structured data
In the paper "Admissible clustering procedures" the authors Van Ness and Fisher (1971) have explained well structured data as follows:
Data is said to be well structured if it has exact tree ...
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Admissibility under the loss function
Suppose $X_1 , ..., X_n$ are random samples of exponential distribution with mean $\theta$. Determine $a$ and $b$ such that $a\sum_{i=1}^n X_i +b$ be admissible under the loss function $L(\theta,\...
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Admissibility of Bayes estimators
I have the following questions. They are not homework problems, but they are things that the professor said that I should wonder about. I suspect that I will have to deal with this on an exam in the ...
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On the proof of admissibility of constant estimators under squared loss
The question concerns the discussion in Wasserman, All of Statistics, Section 13.6. He defines:
An estimator $\hat{\theta}$ is inadmissible if there exists another
rule $\hat{\theta}'$ such that ...
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Why is Wald's decision theory not universally recognized as the foundation of statistics?
This is somewhat ill-defined, but: Why is Wald's decision theory not universally recognized as the foundation of statistics? I gather (or maybe I infer) that it was formulated to put frequentist and ...
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Why is the MLE/OLS estimator so common in regression despite inadmissibility? [closed]
Why is regression so commonly used if the OLS estimator for the vector of regression coefficients is inadmissible under the squared error loss function? Is it because of its historical popularity or ...
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Admissible Estimator for Linear Regression
Is there an admissible estimator for a linear regression model with many parameters without restricting the parameter space?
Admissibility will be with respect to Mean Square Error on the regression ...
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1answer
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showing that $\bar{X}$ is inadmissible by comparing with $\max(\bar{X},2)$ under squared error loss function
suppose $X_1,X_2,\ldots,X_n$ be a random sample of $N(\theta,1), \theta>2$.
how can I show $\bar{X}$ is inadmissible estimator
Compared to $\max(\bar{X},2)$ under Squared error loss function
