Results 41 to 50 of about 1,394,927 (329)
European Journal of Cardio-Thoracic Surgery, 2022 Summary OBJECTIVES The emergence of big cardio-thoracic surgery datasets that include not only short-term and long-term discrete outcomes but also repeated measurements over time offers the opportunity to apply more advanced modelling of outcomes.
Xu Wang +4 more
semanticscholar +1 more source
The development of a simple basal area increment model [PDF]
, 2011 In most cases forest practice in Austria use yield tables to predict the growth of their forests. Common yield tables show the increment of pure even-aged stands which are treated in a way the table developer recommends.
Georg Erich Kindermann
core +2 more sources
Bayesian multimodel inference for geostatistical regression models. [PDF]
PLoS ONE, 2011 The problem of simultaneous covariate selection and parameter inference for spatial regression models is considered. Previous research has shown that failure to take spatial correlation into account can influence the outcome of standard model selection ...
Devin S Johnson, Jennifer A Hoeting
doaj +1 more source
PLoS ONE, 2018 Epigenome-wide association studies seek to identify DNA methylation sites associated with clinical outcomes. Difference in observed methylation between specific cell-subtypes is often of interest; however, available samples often comprise a mixture of ...
Daniel W Kennedy +8 more
doaj +1 more source
Flexible semiparametric mixed models [PDF]
, 2005 In linear mixed models the influence of covariates is restricted to a strictly parametric form. With the rise of semi- and nonparametric regression also the mixed model has been expanded to allow for additive predictors.
Reithinger, Florian, Tutz, Gerhard
core +2 more sources
Reducing Selection Bias in Analyzing Longitudinal Health Data with High Mortality Rates [PDF]
, 2010 Two longitudinal regression models, one parametric and one nonparametric, are developed to reduce selection bias when analyzing longitudinal health data with high mortality rates.
Engel, Charles C. +3 more
core +2 more sources
Variational Bayesian EM Algorithm for Quantile Regression in Linear Mixed Effects Models
MathematicsThis paper extends the normal-beta prime (NBP) prior to Bayesian quantile regression in linear mixed effects models and conducts Bayesian variable selection for the fixed effects of the model.
Weixian Wang, Maozai Tian
doaj +1 more source
Estimating Functional Linear Mixed-Effects Regression Models
, 2016 The functional linear model is a popular tool to investigate the relationship between a scalar/functional response variable and a scalar/functional covariate. We generalize this model to a functional linear mixed-effects model when repeated measurements are available on multiple subjects.
Liu, Baisen, Cao, Jiguo
openaire +2 more sources
, 2017 Crown profile is mostly related to the competition of individual trees in the stands, light interception, growth, and yield of trees. A total of 76 sample trees with a total number of 889 whorls and 3658 live branches were used to develop the outer crown
Yunxia Sun, Hui-lin Gao, Fengri Li
semanticscholar +1 more source
Convergence of Parameter Estimates for Regularized Mixed Linear Regression Models [PDF]
2019 IEEE 58th Conference on Decision and Control (CDC), 2019 We consider {\em Mixed Linear Regression (MLR)}, where training data have been generated from a mixture of distinct linear models (or clusters) and we seek to identify the corresponding coefficient vectors. We introduce a {\em Mixed Integer Programming (MIP)} formulation for MLR subject to regularization constraints on the coefficient vectors.
Wang, Taiyao, Paschalidis, Ioannis Ch.
openaire +2 more sources