Linear mixed model-based approaches have emerged as a more efficient methodology for the analysis of MET data. Recently, these mixed model approaches have become predominant, as they provide a ...

ZURICH— Advanced manufacturing technology will play a key role as the automotive industry continues to transition to mixed-model assembly lines.

“Mixed-model assembly is used regularly across industries, most notably the discrete electronics industry where products such as smart phones with multiple form factors and internal configurations are ...

Abstract: The phylogenetic mixed model is an application of the quantitative‐genetic mixed model to interspecific data. Although this statistical framework provides a potentially unifying approach to ...

As an important part of intelligent manufacturing, robotic mixed-model assembly line needs to cost-effectively adjust its configuration to meet the dynamical manufacturing requirements. However, the ...

Explore the application of a partial time-varying coefficient regression and autoregressive mixed model for analyzing relationships between time series variables and covariates. Discover local ...

We also develop a parametric bootstrap algorithm for small samples. Our strategy can be used to check the adequacy of any distribution for random effects in a wide class of mixed models, including ...

Aiming at the low efficiency and poor timeliness of the configuration on the mixed-model robotic assembly line, this paper proposes a digital twin-based virtual reconfiguration method for the ...

Hello, I am relatively new to Turing.jl and Bayesian in general. I was wondering how I could go about implementing an LMM/GLMM model with a random intercept/slope, I couldn't find the tutorial for ...