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.