Results 41 to 50 of about 985,928 (292)

Adaptive non-parametric estimation in the presence of dependence [PDF]

open access: yes, 2016
We consider non-parametric estimation problems in the presence of dependent data, notably non-parametric regression with random design and non-parametric density estimation. The proposed estimation procedure is based on a dimension reduction. The minimax
Asin, Nicolas, Johannes, Jan
core   +2 more sources

Non-parametric tests

open access: yesSouthwest Respiratory and Critical Care Chronicles, 2014
Shengping Yang, Gilbert Berdine
doaj   +3 more sources

Q residual non-parametric Distribution on Fault Detection Approach Using Unsupervised LSTM-KDE

open access: yesInternational Journal of Prognostics and Health Management
It is well known among practitioner, majority collected data from industrial process plant are unlabeled. The collected historical data if utilize, able to provide vital information of process plant condition.
Nur Maisarah Mohd Sobran   +1 more
doaj   +1 more source

Personalized Selumetinib Dosing in Pediatric Neurofibromatosis Type 1: Insights From a Pilot Therapeutic Drug Monitoring Study

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Objective To evaluate selumetinib exposure using therapeutic drug monitoring (TDM) in pediatric patients with neurofibromatosis type 1 (NF1) and plexiform neurofibromas (PN), assess interpatient pharmacokinetic variability, and explore the relationship between drug exposure, clinical response, and adverse effects.
Janka Kovács   +8 more
wiley   +1 more source

RETRACTED: Sustainable financial dimensions of managing poverty in the era of the COVID-19 pandemic: A developing country perspective

open access: yesFrontiers in Environmental Science, 2022
The COVID-19 pandemic is dangerous to people’s lives and livelihoods, creating immediate obstacles for organizations that support impacted populations. This research concentrates on the consequences for local microfinance institutions in Pakistan, which ...
Shaohua Lu   +4 more
doaj   +1 more source

Hypothesis testing for two population means: parametric or non-parametric test?

open access: yes, 2019
The parametric Welch $t$-test and the non-parametric Wilcoxon-Mann-Whitney test are the most commonly used two independent sample means tests. More recent testing approaches include the non-parametric, empirical likelihood and exponential empirical ...
Alenazi, Abdulaziz   +3 more
core   +1 more source

Outcomes of Live Virus Vaccination in Patients With Vascular Anomalies Being Treated With Sirolimus

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Live vaccination in patients with vascular anomalies (VA) receiving sirolimus remains controversial due to immunosuppressive effects and theoretical risks. Procedure This single‐center retrospective study included patients with VA less than 4 years old at the start of sirolimus therapy who were incompletely vaccinated.
Svatava Merkle   +5 more
wiley   +1 more source

Comparison Non-Parametric Machine Learning Algorithms for Prediction of Employee Talent

open access: yesIJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2021
Classification of ordinal data is part of categorical data. Ordinal data consists of features with values based on order or ranking. The use of machine learning methods in Human Resources Management is intended to support decision-making based on ...
I Ketut Adi Wirayasa   +3 more
doaj   +1 more source

Non-Parametric Inference of Relational Dependence

open access: yesCoRR, 2022
Independence testing plays a central role in statistical and causal inference from observational data. Standard independence tests assume that the data samples are independent and identically distributed (i.i.d.) but that assumption is violated in many real-world datasets and applications centered on relational systems.
Ragib Ahsan   +3 more
openaire   +3 more sources

Non-parametric statistical thresholding for sparse magnetoencephalography source reconstructions. [PDF]

open access: yes, 2012
Uncovering brain activity from magnetoencephalography (MEG) data requires solving an ill-posed inverse problem, greatly confounded by noise, interference, and correlated sources.
Nagarajan, Srikantan S   +2 more
core   +1 more source

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