Results 41 to 50 of about 2,518,110 (330)
Divergence estimation in the presence of incomplete lineage sorting and migration
bioRxiv, 2017 This paper focuses on the problem of estimating a species tree from multilocus data in the presence of incomplete lineage sorting and migration. We develop a mathematical model similar to IMa2 (Hey 2010) for the relevant evolutionary processes which ...
Graham Jones
semanticscholar +1 more source
Insects, 2023 House flies (Muscidae) comprise the most species-rich family of the muscoid grade with over 5000 described species worldwide, and they are abundant in various terrestrial and aquatic ecosystems.
Xin Li +7 more
doaj +1 more source
Dual Divergence Estimators of the Tail Index [PDF]
ISRN Probability and Statistics, 2012 The main purpose of the present paper is to propose a new estimator of the tail index using -divergences and the duality technique. These estimators are explored with respect to robustness through the influence function approach. The empirical performances of the proposed estimators are illustrated by simulation.
Bouzebda, Salim, Cherfi, Mohamed
openaire +3 more sources
On Default Priors for Robust Bayesian Estimation with Divergences [PDF]
Entropy, 2020 This paper presents objective priors for robust Bayesian estimation against outliers based on divergences. The minimum γ-divergence estimator is well-known to work well in estimation against heavy contamination. The robust Bayesian methods by using quasi-posterior distributions based on divergences have been also proposed in recent years.
Tomoyuki Nakagawa, Shintaro Hashimoto
openaire +4 more sources
European Journal of Nuclear Medicine and Molecular Imaging, 2020 Purpose Positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) reveals altered cerebral metabolism in individuals with mild cognitive impairment (MCI) and Alzheimer’s dementia (AD). Previous metabolic connectome analyses derive from groups
Min Wang +9 more
semanticscholar +1 more source
Information-Corrected Estimation: A Generalization Error Reducing Parameter Estimation Method
Entropy, 2021 Modern computational models in supervised machine learning are often highly parameterized universal approximators. As such, the value of the parameters is unimportant, and only the out of sample performance is considered.
Matthew Dixon, Tyler Ward
doaj +1 more source
Duality of Maximum Entropy and Minimum Divergence
Entropy, 2014 We discuss a special class of generalized divergence measures by the use of generator functions. Any divergence measure in the class is separated into the difference between cross and diagonal entropy. The diagonal entropy measure in the class associates
Shinto Eguchi +2 more
doaj +1 more source
Robust small area estimation for unit level model with density power divergence.
PLoS ONE, 2023 Unit level model is one of the classical models in small area estimation, which plays an important role with unit information data. Empirical Bayesian(EB) estimation, as the optimal estimation under normal assumption, is the most commonly used parameter ...
Xijuan Niu, Zhiqiang Pang, Zhaoxu Wang
doaj +1 more source
On Estimating L_2^2 Divergence
, 2014 We give a comprehensive theoretical characterization of a nonparametric estimator for the L_2^2 divergence between two continuous distributions. We first bound the rate of convergence of our estimator, showing that it is √n-consistent provided the densities are sufficiently smooth.
Akshay Krishnamurthy +3 more
openaire +3 more sources
Robust Relative Error Estimation
Entropy, 2018 Relative error estimation has been recently used in regression analysis. A crucial issue of the existing relative error estimation procedures is that they are sensitive to outliers.
Kei Hirose, Hiroki Masuda
doaj +1 more source