From 6eac91bf7bcf3515e661d74b49e8179938bd1488 Mon Sep 17 00:00:00 2001
From: Guillaume Horel <guillaume.horel@serenitascapital.com>
Date: Wed, 7 May 2014 10:50:13 -0400
Subject: add GHquad function, get rid of statmod dependency

---
 R/tranche_functions.R | 32 ++++++++++++--------------------
 1 file changed, 12 insertions(+), 20 deletions(-)

(limited to 'R/tranche_functions.R')

diff --git a/R/tranche_functions.R b/R/tranche_functions.R
index 2e7f0f3..5fa954a 100644
--- a/R/tranche_functions.R
+++ b/R/tranche_functions.R
@@ -1,5 +1,3 @@
-library(statmod)
-
 ## todo:
 ## -investigate other ways to interpolate the random severities on the grid
 ## I'm thinking that at eah severity that we add to the distribution, round it down
@@ -11,22 +9,16 @@ library(statmod)
 ## recovery with 0.1-1 support, so it's not clear that there is a big gain.
 ## - do the correlation adjustments when computing the deltas since it seems to be
 ## the market standard
-hostname <- system("hostname", intern=TRUE)
-
-checkSymbol <- function(name){
-    if(!is.loaded(name)){
-        if(.Platform$OS.type == "unix"){
-            root.dir <- "/home/share/CorpCDOs"
-            dyn.load(file.path(root.dir, "code", "R", paste0("lossdistrib",
-                                                             hostname,
-                                                             .Platform$dynlib.ext)))
-        }else{
-            root.dir <- "//WDSENTINEL/share/CorpCDOs"
-            dyn.load(file.path(root.dir, "code", "R", paste0("lossdistrib",
-                                                             .Platform$dynlib.ext)))
-        }
-    }
+
+GHquad <- function(n){
+    n <- as.integer(n)
+    Z <- double(n)
+    w <- double(n)
+    result <- .C("GHquad", n, Z=Z, w=w)
+    result[[1]] <- NULL
+    return(result)
 }
+
 lossdistrib <- function(p){
     ## basic recursive algorithm of Andersen, Sidenius and Basu
     n <- length(p)
@@ -630,9 +622,9 @@ tranche.pvvec <- function(K, L, R, cs){
 BClossdist <- function(defaultprob, issuerweights, recov, rho, Z, w,
                        N=length(recov)+1, defaultflag=FALSE, n.int=500){
   if(missing(Z)){
-    quadrature <- gauss.quad.prob(n.int, "normal")
-    Z <- quadrature$nodes
-    w <- quadrature$weights
+    quadrature <- GHquad(n.int)
+    Z <- quadrature$Z
+    w <- quadrature$w
   }
   ## do not use if weights are not gaussian, results would be incorrect
   ## since shockseverity is invalid in that case (need to use stochasticrecov)
-- 
cgit v1.2.3-70-g09d2