Results 71 to 80 of about 6,417 (238)

Low complexity two-dimensional digital filters using unconstrained SPT term allocation [PDF]

open access: yes, 1996
Previous work by the authors has demonstrated how circularly symmetric and diamond-shaped low-pass linear phase 2-D FIR filters can be designed using coefficients comprising the sum or difference of two signed power-of-two (SPT) terms.
Redmill, DW, Sriranganathan, S, Bull, DR
core   +1 more source

Simple Synchronous and Asynchronous Algorithms for Distributed Minimax Optimization

open access: yesSICE Journal of Control, Measurement, and System Integration, 2017
Synchronous and asynchronous algorithms are presented for distributed minimax optimization. The objective here is to realize the minimization of the maximum of component functions over the standard multi-agent network, where each node of the network ...
Kenta Hanada   +3 more
doaj   +1 more source

Evaluating cutpoints for the MHI-5 and MCS using the GHQ-12: a comparison of five different methods

open access: yesBMC Psychiatry, 2008
Background The Mental Health Inventory (MHI-5) and the Mental Health Component Summary score (MCS) derived from the Short Form 36 (SF-36) instrument are well validated and reliable scales. A drawback of their construction is that neither has a clinically
Fone David L   +3 more
doaj   +1 more source

Variable Selection in Multistate Models for Correlated Data With Application in a COVID‐19 Vaccination Study

open access: yesStatistics in Medicine, Volume 45, Issue 13-14, June 2026.
ABSTRACT Depicting patient transitions among multiple clinical states is a common objective in health services and epidemiological research. Multistate models (MSM) are the primary analytical approach used in such studies. Although the structure of an MSM is typically determined by the research questions of a specific application, models are typically ...
Jason Mao, Yang Li, Wanzhu Tu
wiley   +1 more source

Multiplicity of Solutions for Neumann Problems for Semilinear Elliptic Equations

open access: yesAbstract and Applied Analysis, 2014
Using the minimax methods in critical point theory, we study the multiplicity of solutions for a class of Neumann problems in the case near resonance. The results improve and generalize some of the corresponding existing results.
Yu-Cheng An, Hong-Min Suo
doaj   +1 more source

Minimaxity of the Method of Regularization of Stochastic Processes

open access: yesThe Annals of Statistics, 1982
The idea of smoothing-spline interpolation is generalized to propose an estimator for the mean function of a stochastic process. A minimax property of the proposed estimator is then demonstrated under the usual squared loss function.
openaire   +2 more sources

Subgroup Identification via Multiple Change Point Detection: Methods and Applications

open access: yesWIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Subgroup identification methods facilitate the discovery of clinically meaningful subpopulations with differing disease progression, improving personalized risk assessment and treatment strategies. ABSTRACT Subgroup identification is a significant research area in statistics and machine learning, aiming to partition a heterogeneous population into more
Yaguang Li   +3 more
wiley   +1 more source

Worst-case estimation for econometric models with unobservable components. [PDF]

open access: yes
A worst-case estimator for econometric models containing unobservable components, based on minimax principles for optimal selection of parameters, is proposed. Worst-case estimators are robust against the averse effects of unobservables.
Esteban Bravo, Mercedes   +1 more
core  

On Noncooperative Games, Minimax Theorems and Equilibrium Problems

open access: yes
In this chapter we give an overview on the theory of noncooperative games. In the first part we consider in detail for zero-sum (and constant-sum) noncooperative games under which necessary and sufficient conditions on the payoff function and different ...
Kassay, G., Frenk, J.B.G.
core   +2 more sources

Covariance Estimation for Wide Data

open access: yesWIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Covariance matrix estimation is fundamental to multivariate analysis, with applications spanning finance, genomics, climate science, and signal processing. This review synthesizes recent advances in high‐dimensional covariance estimation‐thresholding, linear and nonlinear shrinkage, graphical models, and random matrix theory‐under a unifying framework ...
Eran Raviv
wiley   +1 more source

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