Results 101 to 110 of about 52,951 (307)
Bayesian multivariate mixed-scale density estimation [PDF]
, 2015 Although continuous density estimation has received abundant attention in the Bayesian nonparametrics literature, there is limited theory on multivariate mixed scale density estimation.
Antonio Canalea +3 more
core +1 more source
Advanced Science, EarlyView.This diagram illustrates that night shift work disrupts circadian clock genes (like CLOCK, BMAL1) in both humans and mice. This disruption leads to mitochondrial dysfunction (imbalanced fusion/fission proteins) and increased oxidative stress, which is identified as the primary mechanism ultimately causing elevated blood pressure.
Zhaoqiang Jiang +16 more
wiley +1 more source
The projection-based multivariate density estimation
Acta et Commentationes Universitatis Tartuensis de Mathematica, 2004 The paper discusses methods of estimation of the multivariate density function by using statistical estimates of the densities of the univariate sample projections. The Gaussian mixture model is analyzed. Density parametrization is applied and parameter calculation methods based on the parameters of projections are proposed.
Kavaliauskas, Mindaugas +2 more
openaire +2 more sources
logcondens: Computations Related to Univariate Log-Concave Density Estimation [PDF]
Maximum likelihood estimation of a log-concave density has attracted considerable attention over the last few years. Several algorithms have been proposed to estimate such a density. Two of those algorithms, an iterative convex minorant and an active set
Lutz Dümbgen, Kaspar Rufibach
core +1 more source
On the Bayesian analysis of species sampling mixture models for density estimation [PDF]
, 2006 The mixture of normals model has been extensively applied to density estimation problems. This paper proposes an alternative parameterisation that naturally leads to new forms of prior distribution.
Griffin, Jim E.
core
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Normal Reference Bandwidths for the General Order, Multivariate Kernel Density Derivative Estimator [PDF]
This note derives the general form of the approximate mean integrated squared error for the q-variate, th-order kernel density r th derivative estimator. This formula allows for normal reference rule-of-thumb bandwidths to be derived.
Christopher F. Parmeter +1 more
core
Multifactor Interest Rate Environment: [PDF]
, 2007 This paper uses multivariate density estimation (MDE) procedures to investigate the pricing of mortgage-backed securities (MBS) in a multifactor interest rate ...
Robert F. Whitelaw +4 more
core
Advanced Science, EarlyView.We investigate whether Montessori and traditional schooling systems shape the developmental trajectory of large‐scale brain dynamics in different ways. We quantify the arrow of time (“non‐reversibility”) in neural activity during resting state and movie‐watching, revealing distinct maturational patterns.
Elvira del Agua +6 more
wiley +1 more source
Insights into Entropy as a Measure of Multivariate Variability
Entropy, 2016 Entropy has been widely employed as a measure of variability for problems, such as machine learning and signal processing. In this paper, we provide some new insights into the behaviors of entropy as a measure of multivariate variability.
Badong Chen +3 more
doaj +1 more source