Nothing
######################################################################
## Copyright 2012 Nicholas G. Polson, James G. Scott, Jesse Windle
## Contact info: <jwindle@ices.utexas.edu>.
## This file is part of BayesBridge.
## BayesBridge is free software: you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation, either version 3 of the License, or
## (at your option) any later version.
## BayesBridge is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
## You should have received a copy of the GNU General Public License
## along with BayesBridge. If not, see <http:##www.gnu.org/licenses/>.
######################################################################
log.tau.grid = seq(-10, 0, 0.5);
trace.beta <- function(y, X, alpha=0.5, ratio.grid=exp(seq(-20,20,0.1)),
tol=1e-9, max.iter=30, use.cg=FALSE, plot.it=FALSE)
{
X = as.matrix(X);
N = dim(X)[1];
P = dim(X)[2];
L = length(ratio.grid);
beta = array(0, dim=c(L, P));
colnames(beta) = colnames(X)
for (i in 1:L) {
beta[i,] = bridge.EM(y, X, alpha, ratio=ratio.grid[i],
lambda.max=ratio.grid[i]/tol, tol, max.iter, use.cg);
}
log.grid = log(ratio.grid);
width = log.grid[L] - log.grid[1];
ymin = min(beta);
ymax = max(beta);
plot(log.grid, beta[,1], col=1, type="l",
ylim=c(ymin, ymax), xlim=c(log.grid[1]-0.1*width, log.grid[L]),
ylab="Coefficient", xlab="Log Ratio",
main="Coefficients vs. log(ratio)");
if (P > 1) {
for (i in 2:P) {
lines(log.grid, beta[,i], col=i, lty=i/8+1);
}
}
legend("bottomleft", legend=colnames(beta), col=seq(1:P), lty=seq(1:P)/8+1);
list("beta"=beta, "grid"=ratio.grid, "log.grid"=log.grid)
}
trace.beta.mcmc <- function(gb, breaks=10, ss=1:nrow(gb$beta))
{
ratio = gb$tau / gb$sig2^0.5
ratio = ratio[ss];
beta = gb$beta[ss,];
M = nrow(beta);
P = ncol(beta);
xlim = c( min(ratio), max(ratio));
ylim = c( min(beta) , max(beta) );
order.idx = order(ratio)
ratio = ratio[order.idx]
beta = beta[order.idx,];
if (length(breaks)==1) {
sep.idx = floor(seq(1, M, length.out=breaks));
} else {
sep.idx = breaks; breaks = length(sep.idx);
}
bins = breaks - 1;
ratio.fact = ratio;
ratio.mean = rep(0, bins);
beta.mean = matrix(nrow=bins, ncol=P);
ratio.sd = rep(0, bins);
beta.sd = matrix(nrow=bins, ncol=P);
for (i in 1:bins) {
idc = sep.idx[i]:sep.idx[i+1];
ratio.mean[i] = mean(ratio[idc]);
beta.mean[i,] = apply(beta[idc,], 2, mean);
ratio.sd[i] = sd(ratio[idc]);
beta.sd[i,] = apply(beta[idc,], 2, sd);
ratio.fact[idc] = mean(ratio[idc]);
}
xlim = c(ratio.mean[1], ratio.mean[bins]);
plot(xlim[1]-1, ylim[1]-1, xlim=xlim, ylim=ylim, xlab="", ylab="", main="");
title(main="E[beta | tau/sig]", xlab="ratio", ylab="beta");
hsvs.p = hsv(0:P/P, 1.0, 1.0, 0.5);
hsvs.l = hsv(0:P/P, 1.0, 1.0, 0.2)
hsvs.s = hsv(0:P/P, 1.0, 1.0, 0.1)
## pchs = (1:P) %% 15 + 4;
## for (i in 1:P) {
## ## col.i = col2rgb(colors()[i+1]);
## ## rgb.i = rgb(col.i[1], col.i[2], col.i[2], alpha=01, maxColorValue=255);
## points(ratio, beta[,i], col=hsvs[i], pch=pchs[i])
## }
for (i in 1:P) {
## x = ratio.mean;
x = jitter(ratio.mean);
lines(x, beta.mean[,i], col=hsvs.l[i]);
points(x, beta.mean[,i], col=hsvs.p[i], pch=20);
lines(x, beta.mean[,i] + 2 * beta.sd[,i], col=hsvs.l[i]);
lines(x, beta.mean[,i] - 2 * beta.sd[,i], col=hsvs.s[i]);
## points(x, beta.mean[,i], col=hsvs.l[i], pch=1, cex=beta.sd);
## for (j in 1:bins) {
## x.j = rep(x[j], 2);
## y.j = beta.mean[j,i] - 2 * beta.sd[j,i] + c(0,4) * beta.sd[j,i];
## lines(x.j, y.j, col=hsvs.l[i])
## }
}
out = list("ratio.mean"=ratio.mean, "ratio.sd"=ratio.sd, "beta.mean"=beta.mean, "beta.sd"=beta.sd);
}
## It would make more sense to let sig2 be estimated and to put a grid on tau2
## That would be more like the trace plot based upon EM.
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.