iprior2

• This udpate provides a complete redesign of the internals of the package. There are more kernels supported, new estimation methods, and plots are done using the ggplot2 package.
• Enhanced the methods and calculations for the linear (canonical) kernel, the fractional Brownian motion kernel, and the Pearson kernel.
• Added support for the squared exponential kernel and the d-degree polynomial kernel with offset c.
• Newly redesigned kernel loader function kernL(), while still keeping support for the legacy .kernL() function - although there are plans to phase out this in favour of the new one.
• There is now a summary method for ipriorKernel2 objects.
• The legacy kernels Canonical, FBM and Pearson are now referred to as linear, fbm and pearson, but there is backward compatability with the old references.
• parsm option for interactions has been removed - it's hardly likely that this is ever useful.
• rootkern option for Gaussian process regression has been removed. Should use specialised GPR software for this and keep this package for I-priors only.
• order option to specify higher order terms has been removed in favour of polynomial kernels.
• The package now supports the following estimation methods:
  1. Direct minimisation of the marginal deviance;
  2. EM algorithm (efficient closed-form version and the "regular" version);
  3. Combination of direct and EM methods;
  4. A fixed estimation method to obtain the posterior regression function without estimating any hyperparameters; and
  5. The Nystrom kernel approximation method.
• Parallel restarts is supported via control = list(restarts = TRUE). By default it will use the maximum number of available cores to fit the model in parallel from different random initial values.
• New plot functions added: plot_fitted(), plot_predict(), and plot_iter().
• Updated documentation throughout.
• New vignette added which gives an overview of regression modelling using I-priors.