Results 11 to 20 of about 18,112,323 (302)
Prediction in Multivariate Mixed Linear Models [PDF]
JOURNAL OF THE JAPAN STATISTICAL SOCIETY, 2003 Summary: In the multivariate mixed linear model or multivariate components of variance model with equal replications, this paper addresses the problem of predicting the sum of the regression mean and the random effects. When the feasible best linear unbiased predictors or empirical Bayes predictors are used, this prediction problem reduces to the ...
Tatsuka Kubokawa, M. S. Srivastava
openaire +3 more sources
Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation [PDF]
, 2011 Generalized linear mixed models are a widely used tool for modeling longitudinal data. However, their use is typically restricted to few covariates, because the presence of many predictors yields unstable estimates.
Groll, Andreas, Tutz, Gerhard
core +3 more sources
Monitoring of Linear Profiles Using Linear Mixed Model in the Presence of Measurement Errors
Mathematics, 2022 In the application of control charts, most of the research in profile monitoring is based on accurate measurements. Measurement errors, however, often exist in many manufacturing and service environments.
Wenhui Liu, Zhonghua Li, Zhaojun Wang
doaj +1 more source
Sparse probit linear mixed model [PDF]
Machine Learning, 2017 Published version, 21 pages, 6 ...
Stephan Mandt +5 more
openaire +3 more sources
Journal of Forest Science, 2015 Models of height curves generated using a linear mixed effects model and generalized model were compared. Both tested models were also compared with local models of height curves, which were fitted using a nonlinear regression.
Z. Adamec
doaj +1 more source
Generalized linear mixed model for segregation distortion analysis
BMC Genetics, 2011 Background Segregation distortion is a phenomenon that the observed genotypic frequencies of a locus fall outside the expected Mendelian segregation ratio. The main cause of segregation distortion is viability selection on linked marker loci.
Zhan Haimao, Xu Shizhong
doaj +1 more source
Modified BIC Criterion for Model Selection in Linear Mixed Models
Mathematics, 2023 Linear mixed-effects models are widely used in applications to analyze clustered, hierarchical, and longitudinal data. Model selection in linear mixed models is more challenging than that of linear models as the parameter vector in a linear mixed model ...
Hang Lai, Xin Gao
doaj +1 more source
A mixed integer linear programming model for minimum backbone grid
Frontiers in Energy Research, 2023 Developing a minimum backbone grid in the power system planning is beneficial to improve the power system’s resilience. To obtain a minimum backbone grid, a mixed integer linear programming (MILP) model with network connectivity constraints for a minimum
Wenwen Mei +5 more
doaj +1 more source
Journal of Forest Science, 2012 The estimation of forest biomass is important for practical issues and scientific purposes in forestry. The estimation of forest biomass on a large-scale level would be merely possible with the application of generalized single-tree biomass models.
L.Y. Fu +4 more
doaj +1 more source
A Linear Mixed-Effects Model of Wireless Spectrum Occupancy
EURASIP Journal on Wireless Communications and Networking, 2010 We provide regression analysis-based statistical models to explain the usage of wireless spectrum across four mid-size US cities in four frequency bands.
Pagadarai Srikanth, Wyglinski AlexanderM
doaj +2 more sources