A small package containing a 3 step routine for fitting Stan models, and limited diagnostics. For complex models with low to moderate numbers of parameters, where the maximum a-posteriori estimate provides a useful starting point, this approach 'may' allow for faster sampling from the posterior. The optional step 1 uses differential evolution, linking to the DEoptim package. Step 2 then uses a BFGS optimizer from the mize package. Step 3 computes a Hessian, or approximation of the Hessian, and uses this either for: a) directly sampling from, for fast but inaccurate representation of the posterior. b) as the basis for an initial target distribution for an adaptive importance sampling procedure.
Package details |
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Author | Charles Driver |
Maintainer | Charles Driver <driver@mpib-berlin.mpg.de> |
License | GPL-3 |
Version | 0.2.0 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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