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Gaussian Structured Additive Regression provides a flexible framework for additive decomposition of the expected value with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity, and complex interactions between covariates of different types....
Persistent link: https://www.econbiz.de/10014477416
We propose geoadditive survival models for analyzing effects jointly with possibly nonlinear effects of other covariates. Within a unified Bayesian frame work, our approach extends the classical Cox model to a more general multiplicative hazard rate model, augmenting the common linear predictor...
Persistent link: https://www.econbiz.de/10010266134
Survival data oftern contain small area geographical or spatial information, such as the residence of individuals. In many cases the impact of such spatial effects on hazard rates is of considerable substantive interest. Therefore, extensions of known survival or hazard rate models to spatial...
Persistent link: https://www.econbiz.de/10010266231
Functional magnetic resonance imaging (fMRI) has become the standard technology in human brain mapping. Analyses of the massive spatio-temporal fMRI data sets often focus on parametric or nonparametric modeling of the temporal component, while spatial smoothing is based on Gaussian kernels or...
Persistent link: https://www.econbiz.de/10010274234
Gaussian Structured Additive Regression provides a flexible framework for additive decomposition of the expected value with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity, and complex interactions between covariates of different types....
Persistent link: https://www.econbiz.de/10014494996