Coverage Properties of Confidence Intervals for Generalized Additive Model Components

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A general framework for functional regression modelling (2017, methodology): “…2017; 17(1–2): 1–35 advantage of this approach is the availability of CIs and tests using mixed model-based likelihood inference methodology (e.g., Marra and Wood, 2012; Wood, 2013), with close to nominal CI coverages for (generalized) functional responses on simulated data (Ivanescu et al.,…”
Econometric modelling of the regional knowledge production function in Europe (2015, background): “Marra and Wood (2012) suggest that this approach results in better coverage performance.”
The cave of Shadows. Addressing the human factor with generalized additive mixed models (2015, background): “…variance estimation, making for easier confidence interval calculation while at the same time providing good coverage probabilities (Nychka, 1988; Marra and Wood, 2012).1 Given k basis functions, penalization will typically result in a model with effective degrees of freedom less than k: k…”
Shape constrained additive models (2015, methodology): “To use the result we condition on the smoothing parameter estimates: the intervals display surprisingly good coverage properties despite this (Marra and Wood (2012), provide a theoretical analysis which partly explains this).”