Results 11 to 20 of about 1,394,927 (329)
Insight into Genome-Wide Associations of Growth Trajectories Using a Hierarchical Non-Linear Mixed Model [PDF]
BiologyIn applying a hierarchical mixed model to genome-wide association analysis (GWAS) of longitudinal data, dimensionality reduction through modeling repeated measurements improves both computational efficiency and statistical power. Legendre polynomials can
Ying Zhang +3 more
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Gradient boosting for linear mixed models [PDF]
The International Journal of Biostatistics, 2020 Gradient boosting from the field of statistical learning is widely known as a powerful framework for estimation and selection of predictor effects in various regression models by adapting concepts from classification theory.
C. Griesbach +2 more
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Scientific Reports, 2021 Repeated measures studies are frequently performed in patient-derived xenograft (PDX) models to evaluate drug activity or compare effectiveness of cancer treatment regimens. Linear mixed effects regression models were used to perform statistical modeling
Ann L. Oberg +13 more
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Remote Sensing, 2022 Airborne light detection and ranging (lidar) has proven to be a useful data source for estimating forest inventory metrics such as basal area (BA), volume, and aboveground biomass (AGB) and for producing wall-to-wall maps for validation of satellite ...
Schyler Brown +2 more
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Functional Plant Breeding Journal, 2020 This paper presents the state of the art of the statistical modelling as applied to plant breeding. Classes of inference, statistical models, estimation methods and model selection are emphasized in a practical way.
Marcos Deon Vilela de Resende +1 more
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Mathematics, 2022 Geographically Weighted Regression (GWR) is the development of multiple linear regression models used in spatial data. The assumption of spatial heterogeneity results in each location having different characteristics and allows the relationships between ...
Lilis Laome +2 more
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partR2: partitioning R2 in generalized linear mixed models
bioRxiv, 2020 The coefficient of determination R2 quantifies the amount of variance explained by regression coefficients in a linear model. It can be seen as the fixed-effects complement to the repeatability R (intra-class correlation) for the variance explained by ...
M. Stoffel, S. Nakagawa, H. Schielzeth
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Primerjava različnih regresijskih modelov za napovedovanje debelinskega priraščanja jelke
Acta Silvae et Ligni, 2021 We present seven alternative statistical models for modelling tree diameter increment with data from permanent sampling plots. In addition to the polynomial regression model, we present a regression model with added random noise, a mixed linear model ...
Andrej Ficko, Vasilije Trifković
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Double Penalized Expectile Regression for Linear Mixed Effects Model
Symmetry, 2022 This paper constructs the double penalized expectile regression for linear mixed effects model, which can estimate coefficient and choose variable for random and fixed effects simultaneously. The method based on the linear mixed effects model by cojoining double penalized expectile regression.
Sihan Gao +4 more
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On the estimation of variance parameters in non-standard generalised linear mixed models: application to penalised smoothing [PDF]
Statistics and computing, 2018 We present a novel method for the estimation of variance parameters in generalised linear mixed models. The method has its roots in Harville (J Am Stat Assoc 72(358):320–338, 1977)’s work, but it is able to deal with models that have a precision matrix ...
M. Rodríguez-Álvarez +3 more
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