Results 51 to 60 of about 123,209 (248)
In the field of chemical data modeling, it is common to encounter response variables that are constrained to the interval (0, 1). In such cases, the beta regression model is often a more suitable choice for modeling.
Solmaz Seifollahi +2 more
doaj +1 more source
Meta‐analysis fails to show any correlation between protein abundance and ubiquitination changes
We analyzed over 50 published proteomics datasets to explore the relationship between protein levels and ubiquitination changes across multiple experimental conditions and biological systems. Although ubiquitination is often associated with protein degradation, our analysis shows that changes in ubiquitination do not globally correlate with changes in ...
Nerea Osinalde +3 more
wiley +1 more source
High Dimensional Semiparametric Scale-Invariant Principal Component Analysis
We propose a new high dimensional semiparametric principal component analysis (PCA) method, named Copula Component Analysis (COCA). The semiparametric model assumes that, after unspecified marginally monotone transformations, the distributions are ...
Han, Fang, Liu, Han
core +1 more source
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
wiley +1 more source
Fast and Adaptive Sparse Precision Matrix Estimation in High Dimensions
This paper proposes a new method for estimating sparse precision matrices in the high dimensional setting. It has been popular to study fast computation and adaptive procedures for this problem.
Bickel +24 more
core +1 more source
ABSTRACT Objective Status epilepticus (SE) is associated with significant mortality. Sleep architecture may reflect normal brain function. Impaired sleep architecture is associated with poorer outcomes in numerous conditions. Here we investigate the association of sleep architecture in continuous EEG (cEEG) with survival in SE.
Ran R. Liu +5 more
wiley +1 more source
Unsupervised Liu-type shrinkage estimators for mixture of regression models
The mixture of probabilistic regression models is one of the most common techniques to incorporate the information of covariates into learning of the population heterogeneity. Despite its flexibility, unreliable estimates can occur due to multicollinearity among covariates.
Elsayed Ghanem +2 more
openaire +3 more sources
ABSTRACT Objective People with epilepsy (PWE) may experience cognitive deficits but fail to undergo formal evaluation. This study compares cognitive status between PWE and healthy controls in the West African Republic of Guinea. Methods A cross‐sectional, case–control study was conducted in sequential recruitment phases (July 2024–July 2025) at Ignace ...
Maya L. Mastick +14 more
wiley +1 more source
Stochastic Restricted Modified Mixed Logistic Estimator
In this study, we introduce a new estimator named the Stochastic Restricted Modified Mixed Logistic Estimator (SRMMLE), which is specifically designed to handle multicollinearity within the framework of stochastic linear restrictions.
Kayathiri Thayaparan +2 more
doaj +1 more source
AN INVESTIGATION INTO PROPERTIES OF JACKKNIFED AND BOOTSTRAPPED LIU-TYPE ESTIMATOR [PDF]
In 2003, Liu proposed a new estimator dealing with the problem of multicollinearity in linear regression model pointing out a drawback of ridge estimator used in this context. This new estimator, called Liu-type estimator was demonstrated to have lesser mean squared error than ridge estimator and ordinary least squares estimator, however, it may carry
Chaubey, Yogendra P. +2 more
openaire +2 more sources

