uwham.phi: Unbinned weighted histogram analysis method (UWHAM) for...

In UWHAM: Unbinned Weighted Histogram Analysis Method (UWHAM)

Unbinned weighted histogram analysis method (UWHAM) for estimating expectations

Description

This function implements UWHAM for estimating expectations for multiple distributions (such as multiple generalized ensembles) as described in Tan et al. (2012).

Usage

uwham.phi(phi, state, out.uwham, fisher = TRUE)

Arguments

phi	A vector of function (or observable) values on the pooled sample.
state	A vector of indices between 1 to M for the thermodynamic states under which expectations are to be computed.
out.uwham	The output of uwham.
fisher	Logical; if NULL, no variance estimation; if TRUE, variance estimation is based on Fisher information; if FALSE variance estimation is based on the Sandwich variance formula (see the details).

Details

The implementation is directly based on Tan et al. (2012). See the details for uwham.

Value

phi	The vector of estimated expectations.
phi.v	The vector of estimated variances for phi, if fisher!=NULL.
phi.V	The variance-covariance matrix for phi, if fisher!=NULL.

References

Tan, Z., Gallicchio, E., Lapelosa, M., and Levy, R.M. (2012) "Theory of binless multi-state free energy estimation with applications to protein-ligand binding," Journal of Chemical Physics, 136, 144102.

Examples

#See the examples for uwham().

UWHAM documentation built on May 20, 2022, 5:05 p.m.