Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
利用积分嵌套拉普拉斯近似进行潜在高斯模型的近似贝叶斯推断
Summary Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalized) linear models, (generalized) additive models, smoothing spline models, state space models, semiparametric regression, spatial and spatiotemporal models, log-Gaussian Cox processes and geostatistical and geoadditive models. We consider approximate Bayesian inference in a popular subset of structured additive…