un_scale_transform: Reverse Simple Preconditioning Transformation

Description Usage Arguments Value Note Author(s) References See Also

View source: R/Scale_Logistic.R

Description

Applies the reverse of the ‘simple’ preconditioning transformation described within the ‘Implementation Details’ section of Pollock et al. (2016) to points in the transformed space (eta.pos), which are centred such that the origin maps to the point at which the control variate is computed (beta.star). Outputs a vector giving the position within the original space (beta.pos).

Usage

1

Arguments

eta.pos

Point within the transformed space to be reverse transformed to the original space

beta.star

Point within the original space that the control variate is computed at

n.sigma

Simple preconditioning matrix

Value

beta.pos

Point within the original space

Note

As discussed within Pollock et al. (2016) the simple preconditioning procedure uses a diagonal matrix. Modification to this function would be required (along with associated package functions) if the full preconditioning matrix were to be used (precon / precon.inv).

Author(s)

Murray Pollock, Paul Fearnhead, Adam Johansen and Gareth Roberts

References

Pollock, Murray, Paul Fearnhead, Adam M. Johansen, and Gareth O. Roberts. "The scalable Langevin exact algorithm: Bayesian inference for big data." arXiv preprint arXiv:1609.03436 (2016).

See Also

scale_transform


mpoll/scale documentation built on Dec. 9, 2019, 7:15 a.m.