exclusion_thresh: Exclusion threshold function

In sgolchi/BPD: Bayesian Particle Discovery

Description

Exclusion threshold function

Usage

exclusion_thresh(m, G, snew, cnew, covmat, lambda_mean, alpha2, M)

Arguments

m	the mass of Higgs
G	grid over which the signal is evaluated
snew	matrix of signal widths, same dimensions as cnew
cnew	matrix of signal normalizing constants - dimensions are (size of grid G)by(number of categories/channels,41)
covmat	covariance matrix for teh background prior
lambda_mean	mean vector for the background prior
M	number of iterations used to estimate the lower 5 percent quantile of the mass marginal posterior
lambda0	initial backgorund value
y	observations

Value

exclusion threshold for a given mass

Examples

load('data/SMC_full_poly')
L = dim(post2$thetat)[2]
dd_theta = density(post2$thetat[,L])
theta = dd_theta$x[which.max(dd_theta$y)]
dd_tau = density(post2$taut[,L])
tau = dd_tau$x[which.max(dd_tau$y)]
beta = apply(post2$beta[,L,], 2, mean)
xG = (G  - min(G))/(max(G) - min(G))
covmat = Gausscor(xG, theta, tau)
lambda_mean = log(poly(beta, xG)) - tau/2
cg = floor(seq(1, length(G), length = 100))
Qex = sapply(seq(100,180,1), exclusion_thresh,  G[cg], snew, cnew, covmat[cg,cg], lambda_mean[cg], M = 1000)

sgolchi/BPD documentation built on May 19, 2019, 3:05 a.m.