Results 41 to 50 of about 328,528 (303)
ABSTRACT Background Japan has one of the highest dialysis prevalence rates worldwide and a shrinking, aging population. Whether dialysis burden has entered a sustained post‐peak phase or whether recent declines partly reflect pandemic‐related disruptions remains uncertain.
Hatice Şahin +2 more
wiley +1 more source
Model averaging for generalized linear models in fragmentary data prediction
Fragmentary data is becoming more and more popular in many areas which brings big challenges to researchers and data analysts. Most existing methods dealing with fragmentary data consider a continuous response while in many applications the response ...
Chaoxia Yuan, Yang Wu, Fang Fang
doaj +1 more source
Genetic heterogeneity of residual variance - estimation of variance components using double hierarchical generalized linear models [PDF]
Background The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals.
Erling Strandberg +21 more
core +1 more source
Reciprocal control of viral infection and phosphoinositide dynamics
Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley +1 more source
We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee +3 more
wiley +1 more source
Why analyze germination experiments using Generalized Linear Models?
: We compared the goodness of fit and efficiency of models for germination. Generalized Linear Models (GLMs) were performed with a randomized component corresponding to the percentage of germination for a normal distribution or to the number of ...
Fábio Janoni Carvalho +2 more
doaj +1 more source
Partially Linear Generalized Single Index Models for Functional Data (PLGSIMF)
Single-index models are potentially important tools for multivariate non-parametric regression analysis. They generalize linear regression models by replacing the linear combination α0⊤X with a non-parametric component η0α0⊤X, where η0(·) is an unknown ...
Mohamed Alahiane +3 more
doaj +1 more source
Sparsifying Generalized Linear Models
We consider the sparsification of sums $F : \mathbb{R}^n \to \mathbb{R}$ where $F(x) = f_1(\langle a_1,x\rangle) + \cdots + f_m(\langle a_m,x\rangle)$ for vectors $a_1,\ldots,a_m \in \mathbb{R}^n$ and functions $f_1,\ldots,f_m : \mathbb{R} \to \mathbb{R}_+$.
Arun Jambulapati +3 more
openaire +2 more sources
Linear Models are Most Favorable among Generalized Linear Models [PDF]
To appear in the 2020 IEEE International Symposium on Information ...
Kuan-Yun Lee, Thomas A. Courtade
openaire +2 more sources
Regularization and Model Selection with Categorial Predictors and Effect Modifiers in Generalized Linear Models [PDF]
We consider varying-coefficient models with categorial effect modifiers in the framework of generalized linear models. We distinguish between nominal and ordinal effect modifiers, and propose adequate Lasso-type regularization techniques that allow for ...
Gertheiss, Jan +2 more
core +1 more source

