Finally, we employed a generalized additive mixed model to compare trends in VR over time between survivors and non-survivors. A total of 8024 patients were enrolled. Multivariable Cox regression analysis identified a baseline VR >=1.89 as an independent risk factor predicting 30-day mortality (...
Deconvoluting cell-state abundances from bulk RNA-sequencing data can add considerable value to existing data, but achieving fine-resolution and high-accuracy deconvolution remains a challenge. Here we introduce MeDuSA, a mixed model-based method that le
A generalized additive model can be seen as a regression model which is able to model non-linear patterns. Rather than explaining the basic concepts underlying generalized additive modeling at the start, in this tutorial we will explain the concepts when we first need them in the analysis. Impor...
2.1.7.1. Tropical N2O model This empirical statistical model simulates direct N2O emissions from agricultural systems in tropical and sub-tropical regions using a Generalized Additive Mixed Model (GAMM) which allows the effects of multiple covariates to be modeled as linear or smooth non-linear conti...
The usual assumption of a linear-in-parameters utility function in a multinomial logit model is relaxed by a sum of one-dimensional nonparametric functions of the explanatory variables. The model generalizes the logistic regression of the generalized additive model for a binary response to a ...
Generalized Additive Mixed Models (GAMM) were used with the mgcv package (function gamm())53for R, in order to assess (1) the existence of seasonality and temporal trends of HR and DD and (2) the effect of the explanatory variables on HR and DD. GAMMs use a sum of smooth functions ...
We extend the Generalized Extreme Value (GEV) regression model proposed by Calabrese and Osmetti (Journal of Applied Statistics 40(6):1172–1188, 2013) to a Generalized Additive Model (GAM). We suggest to consider the quantile function of the GEV distribution as a link function in a GAM, ...
To date, the statistical approach based on generalized additive model (GAM) and bootstrap has not been used for fault diagnosis in fermentation processes, much less the fermentation process of glutamate with small samples sets. Results: A combined approach of GAM and bootstrap was developed ...
In this section we explain how to estimate a time-varying VAR model using the Generalized Additive Model (GAM) framework, which allows for non-linear relationships between variables (see also Bringmann et al., Citation2018, Citation2017). We leverage the GAM framework for the estimation for time...
International Journal of Geo-Information Article A Generalized Additive Model Combining Principal Component Analysis for PM2.5 Concentration Estimation Shuang Li 1,2 ID , Liang Zhai 2,* ID , Bin Zou 3, Huiyong Sang 2 and Xin Fang 3 1 College of Geomatics, Shandong University of Science and ...