In statistical decision theory, a minimax estimator δ M {\displaystyle \delta ^{M}\,\!} is an estimator which performs best in the worst possible case...

Minimax (sometimes Minmax, MM or saddle point) is a decision rule used in artificial intelligence, decision theory, combinatorial game theory, statistics...

min-max can also refer to: Minimax estimator, an estimator whose maximal risk is minimal between all possible estimators Minimax approximation algorithm...

The James–Stein estimator is an estimator of the mean θ := ( θ 1 , θ 2 , … θ m ) {\displaystyle {\boldsymbol {\theta }}:=(\theta _{1},\theta _{2},\dots...

Estimator", the "Approximately Unbiased Estimator" and "Minimax Estimator", also "A Conditional Mean Squared Error Estimator", and other variations as well. The...

solution of a convex optimization problem gives the optimal, minimax regret-minimizing linear estimator, which can be seen by the following argument. According...

means, the MLE estimator λ ^ i = X i {\displaystyle {\hat {\lambda }}_{i}=X_{i}} is inadmissible. In this case, a family of minimax estimators is given for...

Mexican paradox Microdata (statistics) Midhinge Mid-range MinHash Minimax Minimax estimator Minimisation (clinical trials) Minimum chi-square estimation Minimum...

counterpart is computationally tractable. Stability radius Minimax Minimax estimator Minimax regret Robust statistics Robust decision making Robust fuzzy...

Wolfowitz, J. (1956), "Asymptotic minimax character of the sample distribution function and of the classical multinomial estimator", Annals of Mathematical Statistics...

loss. Leonard J. Savage argued that using non-Bayesian methods such as minimax, the loss function should be based on the idea of regret, i.e., the loss...

{F}}} ; estimation quality varies depending on the distance, but can be minimax-optimal in certain settings. When exact maximization is not available or...

under the supervision of Robert B. Ash with a dissertation on Certain Minimax Estimators of the Mean of a Multivariate Normal Distribution. As chair of statistics...

-nearest neighbour error converges to the Bayes error at the optimal (minimax) rate O ( n − 4 d + 4 ) {\displaystyle {\mathcal {O}}\left(n^{-{\frac {4}{d+4}}}\right)}...

maximum likelihood estimator of the best candidate. if p is close to 1, then the Minimax winner is the maximum likelihood estimator of the best candidate...

from the original on 2008-09-30. Berger, J. O. (1982). "Selecting a Minimax Estimator of a Multivariate Normal Mean". The Annals of Statistics. 10: 81–92...

rule Minimax Loss function Mean squared error Mean absolute error Estimation theory Estimator Bayes estimator Maximum likelihood Trimmed estimator M-estimator...

an unbiased estimator of β {\displaystyle \beta } , and the Gauss-Markov theorem tells us that it is the Best Linear Unbiased Estimator. However, overfitting...

dataset in a conservative manner called minimax sampling. The minimax sampling has its origin in Anderson minimax ratio whose value is proved to be 0.5:...

{{cite journal}}: Cite journal requires |journal= (help) "Special Section: Minimax Shrinkage Estimation: A Tribute to Charles Stein". Statistical Science...

on the error probability of any decoder as well as the lower bounds for minimax risks in density estimation. Let the discrete random variables X {\displaystyle...

"The normal law under linear restrictions: simulation and estimation via minimax tilting". Journal of the Royal Statistical Society, Series B. 79: 125–148...

was particularly known for her work in theoretical statistics on minimax estimators with constrained parameters. MacGibbon became the first woman to chair...

dissertation, supervised by Lucien Le Cam, was titled, "Asymptotically Minimax Estimators for Distributions with Increasing Failure Rate". After starting her...

performance of any analysis on the dataset, e.g. classification. In that regard, minimax sampling ratio can be used to make the dataset robust with respect to uncertainty...

copy as title (link) Y. C. Eldar, A. Beck, and M. Teboulle, "A Minimax Chebyshev Estimator for Bounded Error Estimation," IEEE Trans. Signal Process., 56(4):...

Canadian Journal of Statistics Award in 1990 for his paper "Minimax-variance L- and R-estimators of location". In 2005 he was elected as a Fellow of the American...

1214/009053606000000074. S2CID 7581060. Donoho D, Jin J (2006). "Asymptotic minimaxity of false discovery rate thresholding for sparse exponential data". Annals...

Wolfowitz, J. (1956). "Asymptotic minimax character of the sample distribution function and of the classical multinomial estimator". The Annals of Mathematical...

doi:10.1214/aoms/1177697822. Hwang, J. T. & Casella, George (1982). "Minimax Confidence Sets for the Mean of a Multivariate Normal Distribution" (PDF)...