To reduce the computational burden, we will add options for selecting a subset of representers among all representers 's in the solution (). Inferences on nonparametric functions are usually accomplished using Bayesian confidence intervals. However, they do not provide pointwise coverage, nor a single p-value. Hypothesis tests are only available for simple spline models (Liu et al., 2004; Liu and Wang, 2004). Further research on model selection is also needed. One of our future task is to extend the anova function to perform hypothesis tests for more complicated models, and to compare different models.
Karcher and Wang (2002) proposed the SLM models for correlated non-Gaussian data. Thus we can extend the slm function for non-Gaussian families.