1 files changed, 35 insertions, 0 deletions
diff --git a/R/plot_distributions.R b/R/plot_distributions.R
new file mode 100644
index 00000000..0b369065
--- /dev/null
+++ b/R/plot_distributions.R
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+## some plots
+matplot(Z, cbind(w, w.mod), type="l", ylab="probability density",
+        main="Factor distribution (Gaussian, and Market implied)")
+lossdist <- array(0, dim=c(Ngrid, n.int))
+for(i in 1:n.int){
+    pshocked <- sapply(p[,ncol(p)], shockprob, rho=rho, Z=Z[i])
+    S <- 1 - Rstoch[i,,ncol(p)]
+    lossdist[,i] <- lossrecovdist(pshocked, 0, issuerweights, S, Ngrid)$L
+}
+
+lossdist.orig <- BClossdistC(SurvProb, issuerweights, recov, rho, Ngrid)
+matplot(seq(0,1,0.01), cbind(lossdist.orig$L[,ncol(p)], lossdist%*%w.mod), type="l", xlab="loss percentage",
+        ylab="probability density", main="market implied loss distribution")
+#3d surface of the loss distribution
+Rstoch <- array(0, dim=c(ncol(SurvProb), n.int, n.credit))
+for(t in 1:ncol(SurvProb)){
+    for(i in 1:n.credit){
+        Rstoch[t,,i] <- stochasticrecov(recov[i], 0, Z, w.mod, rho, defaultprob[i,t], p[i,t])
+    }
+}
+
+clusterExport(cl, list("p", "shockprob", "rho", "Z", "lossdistribC.joint", "Rstoch", "lu"))
+
+parf <- function(i){
+    pshocked <- apply(p, 2, shockprob, rho=rho, Z=Z[i])
+    return( lossdistribC.joint(pshocked[,ncol(p)], issuerweights, 1-Rstoch[ncol(p),i,], lu) )
+}
+
+dist <- parSapply(cl, 1:n.int, parf)
+dist <- array(dist, dim=c(1/lu+1, 1/lu+1, 100))
+distw <- array(0, dim=c(1/lu+1, 1/lu+1))
+for(i in 1:n.int){
+    distw <- distw+dist[,,i] * w.mod[i]
+}
+persp(distw, theta=-20, phi=13, col="lightgreen",ticktype="detailed", shade=0.6, expand=0.8, border=NA, ltheta=10)