abctools (version 0.2-2)

selectsumm: Generic function for selecting summary statistics in ABC inference.

Description

The function implements functions which implement summary statistics selection methods.

Usage

selectsumm(obs, param, sumstats, obspar = NULL, ssmethod, verbose = TRUE, 
final.dens = FALSE, ...)

Value

A list with the following components:bestthe best subset(s) of statistics.critvalsthe calculated criterion values (if do.crit=TRUE).errsimulation error (if obspar is supplied and do.err=TRUE).orderthe subsets considered during the algorithm (same as the input do.only.post.samplean array of dimension nacc x npar x ndatasets giving the posterior sample for each observed dataset. Not returned if final.dens=FALSE.sumsubsan index into the subsets considered during the algorithm.

Details

The function is essentially a wrapper for more specific summary selection methods, and is designed to be flexible for future additions and minimization criteria. See the help files for each summary selection method for more details.

References

Blum, M. G. B, Nunes, M. A., Prangle, D. and Sisson, S. A. (2013) A comparative review of dimension reduction methods in approximate Bayesian computation. Stat. Sci. (to appear). Fearnhead, P. and Prangle, D. (2012) Constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation. J. R. Stat. Soc. B 74, Part 3, 1--28. Joyce, P. and P. Marjoram (2008) Approximately sufficient statistics and Bayesian computation. Stat. Appl. Gen. Mol. Biol. 7 Article 26. Nunes, M. A. and Balding, D. J. (2010) On Optimal Selection of Summary Statistics for Approximate Bayesian Computation. Stat. Appl. Gen. Mol. Biol. 9, Iss. 1, Art. 34. Wegmann, D. et al. (2009) Efficient approximate Bayesian computation coupled With Markov chain Monte Carlo Without Likelihood. Genetics 182 (4), 1207--1218. Wegmann, D. et al. (2010) ABCtoolbox: A versatile toolkit for approximate Bayesian computations. BMC Bioinf. 11, 116--123.

See Also

mincrit, AS.select, pls.abc

Examples

# load example data:

data(coal)
data(coalobs)

param<-coal[,2]
simstats<-coal[,4:6]

# use matrix below just in case to preserve dimensions.

obsstats<-matrix(coalobs[1,4:6],nrow=1)

tmp<-selectsumm(obsstats, param, simstats,ssmethod=AS.select,tol=.1,method="rejection",
allow.none=FALSE,inturn=TRUE,hcorr=TRUE)

tmp$best