Results 31 to 40 of about 120,097 (295)
A blocking and regularization approach to high dimensional realized covariance estimation [PDF]
, 2009 We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix ...
Hautsch, Nikolaus +2 more
core +3 more sources
Statistical Theory and Related FieldsThis paper studies the kernel-type distribution estimator based on asymptotically almost negatively associated (AANA, for short) samples. The rate of uniformly strong consistency is established under some mild conditions.
Shipeng Wu +3 more
doaj +1 more source
E-Jurnal Matematika, 2018 Nonparametric regression can be applied for some data types one of them is time series data. The technique of this method is called smoothing technique.
DEWA AYU DWI ASTUTI +2 more
doaj +1 more source
Nonparametric Regression with Common Shocks
Econometrics, 2016 This paper considers a nonparametric regression model for cross-sectional data in the presence of common shocks. Common shocks are allowed to be very general in nature; they do not need to be finite dimensional with a known (small) number of factors.
Eduardo A. Souza-Rodrigues
doaj +1 more source
Network Localization of Fatigue in Multiple Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks ...
Olli Likitalo +12 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah +7 more
wiley +1 more source
Rate of complete second-order moment convergence and theoretical applications
Journal of Taibah University for Science, 2022 The purpose of this work is to present a novel mode of convergence, complete second-order moment convergence with rate, which implies almost complete convergence and gives a smaller rate of convergence.
M. Madi, I. Laroussi
doaj +1 more source
Combining kernel estimators in the uniform deconvolution problem [PDF]
, 2010 We construct a density estimator and an estimator of the distribution function in the uniform deconvolution model. The estimators are based on inversion formulas and kernel estimators of the density of the observations and its derivative.
van Es, Bert
core +2 more sources
The McCance Brain Care Score and Mortality: Evidence From a Large‐Scale Population‐Based Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives This study aimed to examine the relationship between the McCance Brain Care Score (BCS) and mortality in the general population. Methods We conducted a prospective, population‐based cohort study using data from the UK Biobank. Participants with complete data enabling calculation of BCS and full mortality information were included ...
Zhiqiang Xu, Xiaoxiao Wang, Nan Li
wiley +1 more source
Optimal Estimation for the Functional Cox Model
, 2016 Functional covariates are common in many medical, biodemographic, and neuroimaging studies. The aim of this paper is to study functional Cox models with right-censored data in the presence of both functional and scalar covariates. We study the asymptotic
Qu, Simeng, Wang, Jane-Ling, Wang, Xiao
core +1 more source