Results 91 to 100 of about 658,858 (308)
Revista Colombiana de Estadística, 2007 The mixed linear model is characterized using the classic linear model of Gauss-Markov. The multipliers of Lagrange are a tool to obtain the best lineal predictors (BLUP), we shown the results of Searle (1997), where some sums of the best linear unbiased
López Luis Alberto +2 more
doaj
Binary and Ordinal Random Effects Models Including Variable Selection [PDF]
, 2010 A likelihood-based boosting approach for fitting binary and ordinal mixed models is presented. In contrast to common procedures it can be used in high-dimensional settings where a large number of potentially influential explanatory variables is available.
Groll, Andreas, Tutz, Gerhard
core +1 more source
FEBS Letters, EarlyView.Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure +3 more
wiley +1 more source
An Optimization Model for Reducing Pumping Costs in Water Distribution Systems [PDF]
مجله مدل سازی در مهندسیThe architecture of water distribution networks is inherently intricate, encompassing the strategic management of pumping mechanisms, modulation of reservoir water levels, and ensuring the delivery of water to consumers with adequate flow and pressure. A
Abbasali Rezapour
doaj +1 more source
, 2021 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
openaire +1 more source
Diagnostics for generalised linear mixed models [PDF]
Generalized linear mixed models are generalized linear models that include random effects varying between clusters or 'higher-level' units of hierarchically structured data. Such models can be estimated using gllamm.
Sophia Rabe-Hesketh, Anders Skrondal
core
The human gut microbiome across the life course
FEBS Letters, EarlyView.Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero +4 more
wiley +1 more source
Sobre la construcción del mejor predictor lineal insesgado (BLUP) y restricciones asociadas
Revista Colombiana de Estadística, 2007 A través del modelo lineal clásico de Gauss-Markov, se caracteriza el modelo de efectos mixtos, se aplica la técnica de multiplicadores de Lagrange para obtener los mejores predictores lineales (BLUP) y se ilustran los resultados de Searle (1997), donde ...
LUIS ALBERTO LÓPEZ +2 more
doaj
S-estimation and a robust conditional Akaike information criterion for linear mixed models. [PDF]
We study estimation and model selection on both the fixed and the random effects in the setting of linear mixed models using outlier robust S-estimators.
Tharmaratnam, Kukatharmini +1 more
core
Finite Mixtures of Generalized Linear Regression Models [PDF]
, 2007 Generalized linear models have become a standard technique in the statistical modelling toolbox for investigating relationships between variables.
Bettina Grün +3 more
core +1 more source