Results 71 to 80 of about 2,525,472 (291)
On econometric modeling of incomplete data [PDF]
We discuss results on identification and estimation of dynamic models when values of the endogenous variable are regularly missing. The available data are assumed to be sampled at regular intervals of length k and can be linear combinations of the realizations of the variable over a finite number of periods.
Nijman, T.E., Palm, F.C.
openaire +3 more sources
Pattern classification for incomplete data [PDF]
The problem of pattern classification for inputs with missing values is considered. A general fuzzy min-max (GFMM) neural network utilising hyperbox fuzzy sets as a representation of data cluster prototypes is used. It is shown how a classification decisions can be carried out on a subspace of high dimensional input data.
openaire +1 more source
We identified a systemic, progressive loss of protein S‐glutathionylation—detected by nonreducing western blotting—alongside dysregulation of glutathione‐cycle enzymes in both neuronal and peripheral tissues of Taiwanese SMA mice. These alterations were partially rescued by SMN antisense oligonucleotide therapy, revealing persistent redox imbalance as ...
Sofia Vrettou, Brunhilde Wirth
wiley +1 more source
An Information Criterion for Auxiliary Variable Selection in Incomplete Data Analysis
Statistical inference is considered for variables of interest, called primary variables, when auxiliary variables are observed along with the primary variables.
Shinpei Imori, Hidetoshi Shimodaira
doaj +1 more source
Classification of Incomplete Data Using the Fuzzy ARTMAP Neural Network [PDF]
The fuzzy ARTMAP neural network is used to classify data that is incomplete in one or more ways. These include a limited number of training cases, missing components, missing class labels, and missing classes.
Granger, Eric +3 more
core +1 more source
Calpain small subunit homodimerization is robust and calcium‐independent
Calpains dimerize via penta‐EF‐hand (PEF) domains. Using single‐molecule force spectroscopy, we measured the strength and kinetics of PEF–PEF homodimer binding. The interaction is robust, shows a transient conformational step before dissociation, and remains largely insensitive to Ca2+.
Nesha May O. Andoy +4 more
wiley +1 more source
Formal and Informal Model Selection with Incomplete Data
Model selection and assessment with incomplete data pose challenges in addition to the ones encountered with complete data. There are two main reasons for this.
Beunckens, Caroline +2 more
core +1 more source
Mitochondrial remodeling shapes neural and glial lineage progression by matching metabolic supply with demand. Elevated OXPHOS supports differentiation and myelin formation, while myelin compaction lowers mitochondrial dependence, revealing mitochondria as key drivers of developmental energy adaptation.
Sahitya Ranjan Biswas +3 more
wiley +1 more source
A comparison of incomplete-data methods for categorical data [PDF]
We studied four methods for handling incomplete categorical data in statistical modeling: (1) maximum likelihood estimation of the statistical model with incomplete data, (2) multiple imputation using a loglinear model, (3) multiple imputation using a latent class model, (4) and multivariate imputation by chained equations.
van der Palm, D.W. +2 more
openaire +3 more sources
Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley +1 more source

