Results 131 to 140 of about 444,093 (258)
Improved HAC Covariance Matrix Estimation Based on Forecast Errors [PDF]
We propose computing HAC covariance matrix estimators based on one-stepahead forecasting errors. It is shown that this estimator is consistent and has smaller bias than other HAC estimators.
Yu-Wei Hsieh, Chung-Ming Kuan
core
MXene‐Based Room‐Temperature NO2 Gas Sensors: A Meta‐Analysis
This study presents the first comprehensive meta‐analysis of MXene‐based NO2 sensors, decoding 32 study characteristics across 61 peer‐reviewed studies. By isolating materials chemistry as the primary performance driver over device‐level parameters, the authors establish a methodological blueprint and a predictive structure–function map to accelerate ...
Alexander Khort +3 more
wiley +1 more source
CHD8‐Dependent Chromatin Licensing Sustains Trophoblast Stem Cell Transcriptional Programs
In this study, Huang et al., identify chromatin remodeler CHD8 as an essential factor in TSC maintenance and placental development. CHD8‐dependent chromatin accessibility supports the occupancy of key trophoblast TFs and is coupled to KMT2A‐associated H3K4me3 deposition at TSC stem and cell cycle genes, providing a permissive chromatin environment for ...
Yuanyuan Huang +16 more
wiley +1 more source
Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order [PDF]
This paper analyzes the performance of heteroskedasticity-and-autocorrelation-consistent (HAC) covariance matrix estimators in which the residuals are prewhitened using a vector autoregressive (VAR) filter.
Wouter J. den Haan, Andrew T. Levin
core
Bilateral temporal accelerated 40‐Hz tACS improves cognitive function in patients with Alzheimer's disease. Resting‐state fNIRS identifies treatment‐related increases in frontotemporoparietal functional connectivity, which are associated with cognitive improvement. ABSTRACT The temporal lobes are key hubs for memory and cognition.
Rong Guo +10 more
wiley +1 more source
On the estimation of covariance matrices using panel data artificial regressions
The use of artificial regressions to compute the variance of the difference of pairs of panel data estimators that cannot be ranked in terms of efficiency is considered.
Patacchini, Eleonora
core +1 more source
Brain Network Dynamics of Local and Global Predictive Processing in Aging
Separation of concurrent whole‐brain networks in source‐reconstructed magnetoencephalography (MEG) data suggests that healthy aging reorganizes, rather than uniformly attenuates, neural responses elicited from hierarchical auditory violations. Enhanced early sensory deviance processing alongside reduced higher‐order cognitive responses suggests a large‐
Mathias Houe Andersen +9 more
wiley +1 more source
On the estimation of covariance matrices using panel data artificial regressions [PDF]
The use of artificial regressions to compute the variance of the difference of pairs of panel data estimators that cannot be ranked in terms of efficiency is considered.
Patacchini, Eleonora
core
Ultralow‐Energy Analog Reservoir Computing via Reconfigurable 2‐Transistor Memory
This work presents a reconfigurable reservoir‐computing platform based on an oxide InSnZnO two‐transistor cell in which a hold bias selects volatile relaxation for the reservoir or quasi‐non‐volatile multilevel storage for the readout. Multi‐level hold‐bias kernel tune relaxation currents to generate diverse time constants, enriching reservoir states ...
Jeong‐Min Park +11 more
wiley +1 more source
Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices [PDF]
Conditions are derived for the consistency of kernel estimators of the covariance matrix of a sum of vectors of dependent heterogeneous random variables, which match those of the currently best-known conditions for the central limit theorem, as required ...
Jong, R.M. de, Davidson, J.
core

