Results 31 to 40 of about 2,452,838 (337)
Harmonization of Multicenter Cortical Thickness Data by Linear Mixed Effect Model
ObjectiveAnalyzing neuroimages being useful method in the field of neuroscience and neurology and solving the incompatibilities across protocols and vendors have become a major problem. We referred to this incompatibility as “center effects,” and in this
SeungWook Kim +12 more
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The Mixed Liu Estimator in Stochastic Restricted Linear Measurement Error Model
Ghapani and Babdi [1] proposed a mixed Liu estimator in linear measurement error model with stochastic linear restrictions. In this article, we propose an alternative mixed Liu estimator in the linear measurement error model with stochastic linear ...
Jibo Wu
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The best way to understand a linear mixed model, or mixed linear model in some earlier literature, is to first recall a linear regression model. The latter can be expressed as y = Xβ + 𝜖, where y is a vector of observations, X is a matrix of known covariates, β is a vector of unknown regression coefficients, and 𝜖 is a vector of (unobservable random ...
Jiming Jiang, Thuan Nguyen
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The development of a simple basal area increment model [PDF]
In most cases forest practice in Austria use yield tables to predict the growth of their forests. Common yield tables show the increment of pure even-aged stands which are treated in a way the table developer recommends.
Georg Erich Kindermann
core +2 more sources
Text Data Analysis Using Generalized Linear Mixed Model and Bayesian Visualization
Many parts of big data, such as web documents, online posts, papers, patents, and articles, are in text form. So, the analysis of text data in the big data domain is an important task.
Sunghae Jun
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Latitude: A Model for Mixed Linear-Tropical Matrix Factorization
Nonnegative matrix factorization (NMF) is one of the most frequently-used matrix factorization models in data analysis. A significant reason to the popularity of NMF is its interpretability and the `parts of whole' interpretation of its components ...
Hook, James +2 more
core +1 more source
Psychosocial Outcomes in Patients With Endocrine Tumor Syndromes: A Systematic Review
ABSTRACT Introduction The combination of disease manifestations, the familial burden, and varying penetrance of endocrine tumor syndromes (ETSs) is unique. This review aimed to portray and summarize available data on psychosocial outcomes in patients with ETSs and explore gaps and opportunities for future research and care.
Daniël Zwerus +6 more
wiley +1 more source
On the mixed Kibria–Lukman estimator for the linear regression model
This paper considers a linear regression model with stochastic restrictions,we propose a new mixed Kibria–Lukman estimator by combining the mixed estimator and the Kibria–Lukman estimator.This new estimator is a general estimation, including OLS ...
Hongmei Chen, Jibo Wu
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Subset Selection for Linear Mixed Models
AbstractLinear mixed models (LMMs) are instrumental for regression analysis with structured dependence, such as grouped, clustered, or multilevel data. However, selection among the covariates—while accounting for this structured dependence—remains a challenge. We introduce a Bayesian decision analysis for subset selection with LMMs. Using a Mahalanobis
openaire +3 more sources
ABSTRACT Introduction Neuroblastoma (NB) with central nervous system (CNS) metastases is rare at diagnosis, but occurs more often during relapse/progression. Patients with CNS metastases face a dismal prognosis, with no standardized curative treatment available.
Vicente Santa‐Maria Lopez +13 more
wiley +1 more source

