Results 61 to 70 of about 724,462 (280)
Maximum Lilkelihood and Restricted Maximum Likelihood Estimation for a Class of Gaussian Markov Random Fields [PDF]
This work describes a Gaussian Markov random field model that includes several previously proposed models, and studies properties of their maximum likelihood (ML) and restricted maximum likelihood (REML) estimators in a special case.
Victor De Oliveira
core
REDUCTION OF RESTRICTED MAXIMUM LIKELIHOOD FOR RANDOM COEFFICIENT MODELS
, 1994 The restricted maximum likelihood (REML) estimator of the dispersion matrix for random coefficient models is rewritten in terms of the sufficient statistics of the individual regressions.
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Consistency of restricted maximum likelihood estimators of principal components
The Annals of Statistics, 2009 In this paper we consider two closely related problems : estimation of eigenvalues and eigenfunctions of the covariance kernel of functional data based on (possibly) irregular measurements, and the problem of estimating the eigenvalues and eigenvectors of the covariance matrix for high-dimensional Gaussian vectors. In Peng and Paul (2007), a restricted
Paul, Debashis, Peng, Jie
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Molecular Oncology, EarlyView.Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson +9 more
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Mixed Model-Based Hazard Estimation. [PDF]
We propose a new method for estimation of the hazard function from a set of censored failure time data, with a view to extending the general approach to more complicated models.
Cai, T., Hyndman, R.J., Wand, M.P.
core
Molecular Oncology, EarlyView.Glioma cells mainly express the endothelin receptor EDNRB, while EDNRA is restricted to a perivascular tumor subpopulation. Endothelin signaling reduces glioma cell proliferation while promoting migration and a proneural‐to‐mesenchymal transition associated with poor prognosis. This pathway activates Ca2+, K+, ERK, and STAT3 signalings and is regulated
Donovan Pineau +36 more
wiley +1 more source
Nature Communications, 2020 Linear mixed models have bias due to the assumed independence between random effects. Here, the authors describe a genome-based restricted maximum likelihood, CORE GREML, which estimates covariance between random effects.
Xuan Zhou, Hae Kyung Im, S. Hong Lee
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Somatic mutational landscape in von Hippel–Lindau familial hemangioblastoma
Molecular Oncology, EarlyView.The causes of central nervous system (CNS) hemangioblastoma in Von Hippel–Lindau (vHL) disease are unclear. We used Whole Exome Sequencing (WES) on familial hemangioblastoma to investigate events that underlie tumor development. Our findings suggest that VHL loss creates a permissive environment for tumor formation, while additional alterations ...
Maja Dembic +5 more
wiley +1 more source
On non-negative estimation of variance components in mixed linear models
Journal of Advanced Research, 2016 Alternative estimators have been derived for estimating the variance components according to Iterative Almost Unbiased Estimation (IAUE). As a result two modified IAUEs are introduced.
Heba A. El Leithy +2 more
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, 2017 Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum likelihood ...
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