nonlinear mixed effectsThis chapter discusses the use of mixed-effects models for the analysis of pharmacokinetic (PK) and pharmacodynamic (PD) data in the form of longitudinal and/or multilevel hierarchical structures. Simulated PK and PD data are used to illustrate the implementation of three ...
Survival, growth and vulnerability to drought in fire refuges: implications for the persistence of a fire-sensitive conifer in northern Patagonia Pinheiro J, Bates D, DebRoy S, Sarkar D (2011) R Development Core Team 2010, nlme: linear and nonlinear mixed effects models. R package version 3.1...
Linear and Nonlinear Mixed-Effect Models - Penn State :线性和非线性混合效应模型-宾夕法尼亚州立大学 热度: LINEARANDNOLINEARMATERIALEFFECTSON POSTBUCKLINGSTRENGTHOFCORRUGATEDCONTAINERS 1 ThomasJ.Urbanik U.S.DepartmentofAgriculture,ForestService ForestProductsLaboratory ...
The lme4 package for R provides functions to fit and analyze linear mixed models, generalized linear mixed models and nonlinear mixed models. In each of these names, the term “mixed” or, more fully, “mixed effects”, denotes a model that incorporates both fixed- and random- ...
1.1-7: Linear mixed-effects models using Eigen and S4. Software application. 22 23 Benua, L. (1997). Transderivational identity: ... D Bates,M Maechler,B Bolker,... 被引量: 0发表: 2016年 Nonlinear Mixed-Effects Modeling Programs in R (linear and nonlinear mixed-effects model), nlme...
linear and nonlinear mixed effects models with censored response (NLMEC/LMEC) based on the multivariate Student-t distribution, being a flexible alternative ... LA Matos,MO Prates,Ming-Hui Chen,... - 《Statistica Sinica》 被引量: 64发表: 2013年 加载更多研究...
Linear And Nonlinear Models 作者: Grafarend, Erik W.出版社: Walter De Gruyter Inc页数: 752定价: 198装帧: HRDISBN: 9783110162165豆瓣评分 目前无人评价 评价: 写笔记 写书评 加入购书单 分享到 推荐 我来说两句 短评 ··· 热门 还没人写过短评呢 我要写书评 Linear And Nonlinear Models的书评 ...
treat the randomcoefficients as missing data and apply the EMalgorithm, or apply Newton’s method to the marginal likleihood obtained by minimizing the full likelihood over β [1]. Models for nonlinear mixed effects models are discussed in [2]. We illustrate the various options with a sma...
models for longitudinal data: linear mixed-effects models and structural equation models. Both classes of models allow analyzing quantitative longitudinal data and explicitly define parameters related to both stability and change processes. The models also allow studying interactions between individual and ...
Crossed random effects models (CREMs) are particularly useful in longitudinal data applications because they allow researchers to account for the impact of dynamic group membership on individual outcomes. However, no research has determined what data conditions need to be met to sufficiently identify th...