Mixed effects regression model
The Value of a Statistical Life: A Meta-Analysis with a Mixed Effects Regression Model
... The first section presents the willingness-to-pay (WTP) approach. This approach is based on an individual’s willingness to pay to reduce the risk of death or on his willingness to accept a certain amount to see his life ...
60
Phenomenological modeling of tumor diameter growth based on a mixed effects model
... classic regression approaches, the model parameters are sup- posed to be identical for all ...each model parameter as a sum of fixed and random ...so-called mixed effects models (or ...
30
Extension to mixed models of the Supervised Component-based Generalised Linear Regression
... ear Mixed Model ...random effects used to introduce the dependence between statistical ...that regression demands ...to model Y and capture relevant structural information in ...the ...
13
Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model
... nonlinear mixed models, the problem is more complex, the estimation of such model parameters being difficult even without censored ...the regression function in the ran- dom effects, the ...
25
Population model of bladder motion and deformation based on dominant eigenmodes and mixed-effects models in prostate cancer radiotherapy
... MANUSCRIPT model individual geometric variations of the ...population-based model of the CTV for prostate ...population model of CTVs for rectum cancer, as did (Budiarto et ...to model both ...
47
Model selection and estimation of a component in additive regression
... additive model and a noise admitting a moment of order larger than 8. Pursuant to this work, Brunel and Comte [ 14 ] have also proposed a nonasymptotic iterative method to achieve the same goal. Combining ideas ...
44
Model selection via the lasso in conditional logistic regression
... Marta Avalos Biostatistics team of INSERM U897 and University of Bordeaux 2, France marta.avalos@isped.u-bordeaux2.fr We propose a model selection procedure in the context of matched case-control studies and, more ...
2
Efficient Estimation of Multidimensional Regression Model using Multilayer Perceptrons
... non-linear regression, multivariate regression, multilayer Percep- trons, asymptotic normality 1 Introduction Let us consider a sequence (Yt, Zt) t∈N of ...the model can be written ...
17
Source-Code Level Regression Test Selection: the Model-Driven Way
... leverages Model-Driven Engineering (MDE) for improving RTS in terms of its reusability and ...of model-driven program analysis techniques has proven this approach to be suitable for tracing down the ...
21
Pharmacokinetic similarity of biologics: analysis using nonlinear mixed-effects modeling.
... nonlinear mixed effects models ...the model: the area under the curve and the maximal ...one-compartment model, epoetin alpha PK by a two-compartment model with linear and ...
34
Asymptotic criteria for designs in nonlinear regression with model errors
... Here we restrict our attention to the particular case that {x k } ∞ k=1 is obtained by independent random sampling from ξ. This allows to obtain complete proofs of asymptotic properties of ˆ θ (N ) in a much simpler way ...
10
Fixed versus Random Effects in Poisson Regression Models for Claim Counts
... fixed effects model) or the Zero-Inflated models also deserve consideration for the analysis of claim ...these regression models, ...to model the amount of ...
17
Paint line sequencing in mixed-model assembly lines
... Assembly line layout model B3 B2 Assembly Station Buf f er Up Stream Down Stream Line B Line A Line C Line D B1 Buf f er Buffer Paint line Subassembly line. Main assembly line[r] ...
18
Main effects and interactions in mixed and incomplete data frames
... main effects and ...between effects of covariates on the observations which are independent of the other covari- ates (main effects), and effects of covariates on the observations which depend ...
66
Model selection and estimation of a component in additive regression
... Abstract . Let Y ∈ R n be a random vector with mean s and covariance matrix σ 2 Pn t Pn where Pn is some known n × n-matrix. We construct a statistical procedure to estimate s as well as under moment condition on Y or ...
45
A linear regression model for marine propeller optimization, prototyping and design
... RESULTS AND DISCUSSION Application case for the newly developed model To test the method and its implementation, a set of propeller propulsive performance data was used [Yossifov et al. 1989]. Figure 2 shows a ...
6
Asymptotic Behavior for the Extreme Values of a Linear Regression Model
... a model simpler than (1) using a linear transformation Proposition 1 Let (V i ) be a sequence of iid rvs, (c n > 0) and (d n ) two sequences of IR such that for all continuity point x of ...
16
Ant Colony based model selection for functional-input Gaussian process regression
... the model, along with the type of kernel ...the model, has a strong impact on its prediction capability and the ideal setting might not be ...process model, however, its principles are easily ...
18
A Structural Analysis of the Correlated Random Coefficient Wage Regression Model
... programming model of schooling decisions with 8 unknown types of individuals, where each type is characterized by a speci¯c log wage regression function (linear) as well as a speci¯c utility of attending ...
36
Statistical prediction of aircraft trajectory : regression methods vs point-mass model
... the regression methods perform significantly better than the point-mass ...point-mass model uses the same standard values for most parameters (mass, power reduction, target speeds) for all ...linear ...
11