risk_theta_vect: Expected risk based on a posterior sample
In pauwels2014: Bayesian Experimental Design for Systems Biology.

Description Usage Arguments Value Author(s) See Also Examples

The function computes the expected risk based on the empirical distribution defined by the sample thetas_trans.

1	risk_theta_vect(thetas_trans, n_params)

`thetas_trans`	A matrix which row represent parameter values in physical space (after applying `transform_params`).
`n_params`	The number of parameters to be estimated

A numerical value

Edouard Pauwels

risk_theta_fun

data(knobjs)
sapply(	
	1:length(knobjs),
	function(k){
		assign(names(knobjs)[k], knobjs[[k]], envir = .GlobalEnv)
	}
)

thetas <- knobjActMult1$datas[[1]]$thetas[1:10,]

thetas_trans <- t(apply(thetas, 1, transform_params))
risk_theta_vect(thetas_trans, 9)