Results 101 to 110 of about 45,420 (307)

Smoothing Estimation of Parameters in Censored Quantile Linear Regression Model

open access: yesMathematics
In this paper, we propose a smoothing estimation method for censored quantile regression models. The method associates the convolutional smoothing estimation with the loss function, which is quadratically derivable and globally convex by using a non ...
Mingquan Wang   +5 more
doaj   +1 more source

Electroacupuncture Improves the Learning and Memory by Modulating Hippocampal Glucose Metabolism through IGF1/IGF1R Signaling in Alzheimer's Disease

open access: yesAdvanced Science, EarlyView.
Electroacupuncture (EA) ameliorates learning and memory function in 5×FAD mice by regulating the brain glucose metabolic network. This neuroprotective effect is closely related to enhancing neuronal energy utilization via the IGF1/IGF1R signaling pathway.
Shengxiang Liang   +12 more
wiley   +1 more source

A Bayesian approach to parameter estimation for kernel density estimation via transformations [PDF]

open access: yes
In this paper, we present a Markov chain Monte Carlo (MCMC) simulation algorithm for estimating parameters in the kernel density estimation of bivariate insurance claim data via transformations.
David Pitt   +3 more
core  

On Determination Method for Resolution of Secondary Electron Images in Scanning Electron Microscopy

open access: yesAdvanced Science, EarlyView.
An idealized SEM, termed Rayleigh's microscope, is constructed by Monte Carlo simulation to represent imaging conditions that just satisfy the Rayleigh criterion. Based on this physically defined model, sharpness–resolution conversion curves are established and combined with the Rose criterion, enabling automated resolution evaluation from practical ...
Tongfang Yang, Yanbo Zou, Zejun Ding
wiley   +1 more source

Integrating Lipschitz Extensions and Probabilistic Modelling for Metric Space Classification

open access: yesMathematics
Lipschitz-based classification provides a flexible framework for general metric spaces, naturally adapting to complex data structures without assuming linearity.
Roger Arnau   +2 more
doaj   +1 more source

Optimized smoothing kernels for smoothed particle hydrodynamics

open access: yesAstronomy & Astrophysics
We present a set of new smoothing kernels for smoothed particle hydrodynamics (SPH) that improve the convergence of the method without any additional computational cost. These kernels are generated through a linear combination of other SPH kernels combined with an optimization strategy to minimize the error in the Gresho-Chan vortex test case.
Robert Wissing   +4 more
openaire   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

open access: yesAdvanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia   +7 more
wiley   +1 more source

Empirical and Kernel Estimation of the ROC Curve

open access: yesActa Universitatis Lodziensis. Folia Oeconomica, 2015
The paper presents chosen methods for estimating the ROC (Receiver Operating Characteristic) curve, including parametric and nonparametric procedures.
Aleksandra Katarzyna Baszczyńska
doaj  

Cis‐ and Trans‐Regulatory Factors Independently Shape Phenotypic Heterogeneity of Retinitis Pigmentosa

open access: yesAdvanced Science, EarlyView.
A zebrafish model carrying an identical human RHO S334X allele reveals two independent genetic layers shaping retinitis pigmentosa (RP) severity: a protective 3‐bp cis‐regulatory insertion that attenuates transgene expression, and a dominant trans‐acting modifier that restores a severe phenotype.
Cong Cui   +9 more
wiley   +1 more source

Bias in nearest-neighbor hazard estimation [PDF]

open access: yes
In nonparametric curve estimation, the smoothing parameter is critical for performance. In order to estimate the hazard rate, we compare nearest neighbor selectors that minimize the quadratic, the Kullback-Leibler, and the uniform loss.
Weißbach, Rafael, Dette, Holger
core  

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