A Generalized Additive Model for Discrete-Choice Data - Abe - 1999 () Citation Context ...ude protocol methods (e.g., Payne, Bettman, and Johnson 1988), self-reports (e.g., Johnson 1987; Swait 2001), and non-linear models of compensatory and non-compensatory judgments (e.g., ...
Fisheries observer data were used to develop a Generalized Additive Model (GAM) to estimate rates of observable interactions of hard-shelled turtles. These ... KT Murray - 《Fisheries Research》 被引量: 50发表: 2011年 Objective Bayesian Model Selection in Generalized Additive Models With Penalized...
(Unmeth) and IM regions in five different cell types using a generalized additive model (GAM; grey outlines indicate 95% confidence interval (CI); *donor for histone ChIP-seq does not match donor used in IM analysis). (d) Comparison of DHS signals between Meth, Unmeth and IM regions (...
Background Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points....
This paper is the attempt to summarize the state of art in additive and generalized additive models (GAM). The emphasis is on approaches and numerical procedures which have emerged since the monograph of Hastie and Tibshirani (1990) although reconsidering certain aspects of their work. Apart from...
The propensity scores have been estimated by means of a Generalized Additive Model with a logit as the link function while the matching, to ensure a similar distribution of all the covariates across prescription groups, has been done using the nearest neighbor matching modality56. To ensure a ...
Train a generalized additive model (GAM). GAMMdl = fitcgam(creditrating,"Rating",...PredictorNames=predictorNames); GAMPredictions = resubPredict(GAMMdl); resubLoss(GAMMdl) ans = 0.0542 GAMMdlachieves better accuracy on the training data set. ...
We also examined the predictive ability of two other types of data-driven models: generalized additive models (GAMs) and multivariate adaptive regression splines (MARS). We used data on 9484 patients admitted to hospital with an AMI in Ontario. We used repeated split-sample validation: the data...
Generalized Additive Models: An Introduction with R (Chapman and Hall/CRC, 2017). Guo, J. et al. rstan: R interface to Stan. R package version 2.32.3 https://CRAN.R-project.org/package=rstan (2022). Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for ...
Fitted surfaces of distance to the dam (i.e., contour plots) were added to the ordination model [ordisurf function, R package vegan (Oksanen, 2017), using thin-plate splines in a generalized additive model – GAM (Marra and Wood, 2012, Wood, 2004) to fit values of variables in ...