Results 31 to 40 of about 6,398 (252)

Comparative Evaluation of Nonparametric Density Estimators for Gaussian Mixture Models with Clustering Support

open access: yesAxioms
The article investigates the accuracy of nonparametric univariate density estimation methods applied to various Gaussian mixture models. A comprehensive comparative analysis is performed for four popular estimation approaches: adaptive kernel density ...
Tomas Ruzgas   +3 more
doaj   +1 more source

Probability density estimation from optimally condensed data samples [PDF]

open access: yes, 2003
The requirement to reduce the computational cost of evaluating a point probability density estimate when employing a Parzen window estimator is a well-known problem.
Chao, H., Girolami, M.
core   +1 more source

Neuron‐Derived MIF Engages VCAM1 to Fuel a Self‐Amplifying CXCL8 Loop That Drives Perineural Invasion and Metastasis in Gastric Cancer

open access: yesAdvanced Science, EarlyView.
Neuron‐derived MIF binds VCAM1 on gastric cancer cells and activates ERK/STAT3 signaling, leading to CXCL8 transcription and secretion. Tumor‐derived CXCL8 subsequently stimulates neuronal CXCR2 to enhance MIF production, establishing a self‐amplifying MIF–VCAM1–CXCL8 positive‐feedback loop that promotes perineural invasion, tumor progression, and ...
Xunjun Li   +13 more
wiley   +1 more source

Vendor Types, Attendance, Experience and Sales 2019–2021: Evidence From Five Rural Oregon Farmers Markets

open access: yesAgribusiness, EarlyView.
ABSTRACT Farmers markets provide a direct‐to‐consumer marketing path for farmers and small businesses, facilitating customer discovery and product refinement. This paper explores farmers markets as a business incubator, with a focus on beginning vendors and resilience to a shock, namely, COVID‐19 market restrictions.
Mallory L. Rahe   +2 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia   +1 more
wiley   +1 more source

Electrocardiographic and Skin Manifestations of Turner Syndrome: Association With Cardiovascular Disease

open access: yesAmerican Journal of Medical Genetics Part A, EarlyView.
ABSTRACT Congenital heart disease (CHD) and dermatologic conditions such as lymphedema and acquired melanocytic nevi (AMN) are common in Turner Syndrome (TS). We hypothesized that abnormalities of cranial neural crest cell derivatives drive the skin and heart manifestations of TS. We conducted joint cardiac and skin examinations of volunteers at a 2023
Sarah Elsaim   +8 more
wiley   +1 more source

Posterior asymptotics of nonparametric location-scale mixtures for multivariate density estimation

open access: yesBernoulli, 2017
Density estimation represents one of the most successful applications of Bayesian nonparametrics. In particular, Dirichlet process mixtures of normals are the gold standard for density estimation and their asymptotic properties have been studied extensively, especially in the univariate case.
CANALE, ANTONIO, De Blasi, Pierpaolo
openaire   +3 more sources

Advances in causal discovery methods for ecological time series

open access: yesBiological Reviews, EarlyView.
ABSTRACT Recent advances in data collection technologies (e.g. automated sensor networks, satellite remote sensing, and high‐throughput sequencing) have greatly expanded the availability of ecological time series, enabling new opportunities for causal analyses in dynamic ecosystems.
Kenta Suzuki   +6 more
wiley   +1 more source

Weak conditions for shrinking multivariate nonparametric density estimators

open access: yesJournal of Multivariate Analysis, 2013
Nonparametric density estimators on R^K may fail to be consistent when the sample size n does not grow fast enough relative to reduction in smoothing. For example a Gaussian kernel estimator with bandwidths proportional to some sequence h"n is not consistent if nh"n^K fails to diverge to infinity. The paper studies shrinkage estimators in this scenario
openaire   +1 more source

Nonparametric density estimation for multivariate bounded data using two non-negative multiplicative bias correction methods [PDF]

open access: yesComputational Statistics & Data Analysis, 2015
Discussion Paper / SFB 823;39 ...
Benedikt Funke, Rafael Kawka
openaire   +2 more sources

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