Results 241 to 250 of about 1,302,502 (286)
Electronic Structure Reorganization in MPS3 via d‐Shell‐Selective Alkali Metal Doping
Alkali metal doping of layered MPS3 antiferromagnets reveals d‐shell‐selective responses. While MnPS3 resists charge transfer due to its half‐filled 3d5 shell, FePS3 and NiPS3 behave similarly to CoPS3 by accommodating extra d‐electrons. Yet only CoPS3, with its least stable d‐shell, undergoes pronounced band restructuring and a semiconducting‐to ...
Jonah Elias Nitschke +12 more
wiley +1 more source
Heuristically Adaptive Diffusion‐Model Evolutionary Strategy
Building on the mathematical equivalence between diffusion models and evolutionary algorithms, researchers demonstrate unprecedented control over evolutionary optimization through conditional diffusion. By training diffusion models to associate parameters with specific traits, they can guide evolution toward solutions exhibiting desired behaviors ...
Benedikt Hartl +3 more
wiley +1 more source
Testing and Quantifying Site-Level Variability in Diagnostic Sensitivity of an Anchor Variable. [PDF]
Baek S, Ma Y, Garcia TP.
europepmc +1 more source
Consensus Formation and Change are Enhanced by Neutrality
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag +3 more
wiley +1 more source
Refining estimation techniques for the Two-Sided Power Distribution: A data-sensitive perspective. [PDF]
Güral Y.
europepmc +1 more source
Efficient EM Estimation for the Pogit Model via Polya-Gamma Augmentation. [PDF]
Gutiérrez I, Ramírez S, Jofré L.
europepmc +1 more source
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2001
Abstract Given x 1 ,..., xn from N (θ, σ2) where σ2 is unknown, we can obtain an appropriate likelihood for θ by profiling over σ2. What if the normal assumption is in doubt, and we do not want to use any specific parametric model? Is there a way of treating the whole shape of the distribution as a nuisance parameter, and still get a ...
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Abstract Given x 1 ,..., xn from N (θ, σ2) where σ2 is unknown, we can obtain an appropriate likelihood for θ by profiling over σ2. What if the normal assumption is in doubt, and we do not want to use any specific parametric model? Is there a way of treating the whole shape of the distribution as a nuisance parameter, and still get a ...
+5 more sources
2021
In this paper, we present a robust version of the empirical likelihood estimator for semiparametric moment condition models. This estimator is obtained by minimizing the modified Kullback-Leibler divergence, in its dual form, using truncated orthogonality functions. Some asymptotic properties regarding the limit laws of the estimators are stated.
Amor Keziou, Aida Toma
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In this paper, we present a robust version of the empirical likelihood estimator for semiparametric moment condition models. This estimator is obtained by minimizing the modified Kullback-Leibler divergence, in its dual form, using truncated orthogonality functions. Some asymptotic properties regarding the limit laws of the estimators are stated.
Amor Keziou, Aida Toma
openaire +1 more source
Biometrika, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Jackknife Empirical Likelihood
Journal of the American Statistical Association, 2009Empirical likelihood has been found very useful in many different occasions. However, when applied directly to some more complicated statistics such as U-statistics, it runs into serious computational difficulties. In this paper, we introduce a so-called jackknife empirical likelihood (JEL) method. The new method is extremely simple to use in practice.
Jing, Bing-Yi, Yuan, Junqing, Zhou, Wang
openaire +3 more sources

