added an S3 interface for parameter transformations, see make_transformation, validate_transformation, default_transformation, and any aghq package function with a transformation argument. Providing transformation to aghq and related functions does not change the computation of the marginal likelihood/normalizing constant, but it does mean all downstream summary methods will return results for the transformed parameters.
added an S3 interface for computing moments of positive functions, see make_moment_function, validate_moment, and the updated compute_moment.
added algorithms for moments and marginal posteriors that are now proved to recover the same rate of convergence of the marginal likelihood/normalizing constant. See the updated documentation and options for the default_control() family of functions.
sample_marginal.marginallaplace was using numeric indexing to pull “theta” parameters, and this was not being done correctly. Switched to using named parameters, because this feature was previously added to the summary methods so it was easy to add here.
Added a call to make.unique in marginal_laplace_tmb. TMB uses non-unique names for its par vectors when parameters are supplied to the template as vectors rather than scalars. This was causing errors in the named indexing.
added SIMPLIFY = FALSE to mapply in sample_marginal to fix a problem when the output was only length 1.
interpolation argument in compute_quantiles to auto, from polynomial. I guess this may be considered a bug fix.Added support for doing the multiple required Cholesky decompositions in parallel in sample_marginal.marginallaplace.
Switched from using chol to using Matrix::Cholesky with perm = TRUE inside sample_marginal.marginallaplace.
Added spline-based interpolation to interpolate_marginal_posterior and all downstream functions. Now the calculation of marginals doesn’t get less stable as more quadrature points are added. Added package splines to Imports to support this; since polynomial interpolation almost always gives unstable answers when the number of quadrature points is even moderate, I consider this a necessary Import.
Added the option interpolation to default_control() (see documentation). Default option of auto designed to always give stable marginal posterior interpolation regardless of the number of quadrature points.
Added an internal validate_control check to all functions which use a control argument, which makes sure the user inputs a control list with the correct names and value types. This is supported by the existing control functions, and helps prevent further cryptic downstream errors.
Added a onlynormconst option to aghq and related functions. Simply returns the numeric value of the log integral, avoiding all the extra stuff, at greater speed.
Added a new summary method for objects of class marginallaplace, that includes information on the random effects.
Preserve variable names in all summary output.
Added a requireNamespace condition to all functions from packages listed in Suggests.
aghq::laplace_approximation() had a typo and was returning the wrong value. This has been fixed and tests added for its accuracy based on an example with a known answer.
Fixed an issue in the optimization where the trustOptim package was not being checked for, and this was throwing a cryptic error.
Changed default options for optimization in all functions to optim(...method = 'BFGS'), in case users do not have the trust or trustOptim packages installed.
Added expm1 to logdiffexp() to improve numerical stability.
Fixed optimize_theta so that control arguments are passed correctly.
Removed several unit tests that were failing on M1 Macs. These tests were actually testing that polynomial interpolation of marginal posteriors FAILs, so apparently this isn’t failing on these new Macs, but that’s better, not worse. Will re-test and potentially add back once I have local access to this hardware.
Re-added numDeriv as an Import, since it is used in core functionality.
Switched default optimization control arguments to use base::optim, to facilitate removal of trustOptim and trust as Import dependencies.
Switched default method for numerically differentiated Hessians to 'Richardson', for more accurate results.
Added new function marginal_laplace_tmb() which improves compatibility with the TMB package.
Turned all the main functions for computing posterior summaries into S3 methods with methods for objects of class aghq.
default_control_tmb() which was missing the ndConstruction = 'product' default argument which caused the function to throw a cryptic error.Removed external dependencies:
matrixStats: the only function I had used was logSumExp, which I replaced with a slower but completely base R version from https://stats.stackexchange.com/questions/381936/vectorised-computation-of-logsumexp (accessed on 2021/03/27) in order to remove this dependency. This does not have a meaningful effect on the performance of aghq.
All ‘tidyverse’ subsidiary packages.