{X}},} an estimator (estimation rule) δ M {\displaystyle \delta ^{M}\,\!} is called minimax if its maximal risk is minimal among all estimators of θ {\displaystyle...

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

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

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

The James–Stein estimator is a biased estimator of the mean, θ {\displaystyle {\boldsymbol {\theta }}} , of (possibly) correlated Gaussian distributed...

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...

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...

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...

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...

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:...

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

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...

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

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...

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

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

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):...

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

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

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

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...

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...

Specific tests Bayesian inference Bayesian probability prior posterior Credible interval Bayes factor Bayesian estimator Maximum posterior estimator...

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

[citation needed] In estimation theory of statistics, "statistic" or estimator refers to samples, whereas "parameter" or estimand refers to populations...

Anthropic EleutherAI Google DeepMind Hugging Face Kuaishou Meta AI Mila MiniMax Mistral AI MIT CSAIL OpenAI Runway xAI Architectures Neural Turing machine...

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