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Using linear mixed model and dummy variable model approaches to construct compatible single-tree biomass equations at different scales – A case study for Masson pine in Southern China
aboveground biomass dummy variable model linear mixed model Pinus massoniana
2015/4/14
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 applic...
Efficient computation with a linear mixed model on large-scale data sets with applications to genetic studies
Efficient computation a linear mixed model on large-scale data sets applications genetic studies
2012/9/19
Motivated by genome-wide association studies we consider astan-dard linear model with one additional random effect in situations where many predictors have been collected on the same subjects and each...
A Note on an R^2 Measure for Fixed Effects in the Generalized Linear Mixed Model
Goodness-of-fit Correlated data Model selection Multiple correlation Maximum likelihood Nonnormal distribution
2010/11/8
Using the LRT statistic, a model V# is proposed for the generalized linear mixed model for
assessing the association between the correlated outcomes and fixed effects. The V# compares
the full model...
Analysis of 24-Hour Ambulatory Blood Pressure Monitoring Data using Orthonormal Polynomials in the Linear Mixed Model
Cubic Spline DASH Study Graphical Display
2010/10/19
The use of 24-hour ambulatory blood pressure monitoring (ABPM) in clinical practice and observational epidemiological studies has grown considerably in the past 25 years. ABPM is a very effective tech...
Generalised linear mixed model analysis via sequential Monte Carlo sampling
generalised additive models longitudinal data analysis nonparametric regression sequential Monte Carlo sampler
2009/9/16
We present a sequential Monte Carlo algorithm for the Bayesian analysis of generalised linear mixed models (GLMMs). These models support a variety of interesting regression-type analyses, but performi...