--- /dev/null
+C Output from Public domain Ratfor, version 1.0
+ subroutine sslvrg(penalt,dofoff,x,y,w,ssw, n, knot,nk,coef,
+ * sz,lev, crit,icrit, lambda, xwy, hs0,hs1,hs2,hs3,
+ * sg0,sg1,sg2,sg3, abd,p1ip,p2ip,ld4,ldnk,info)
+
+C Purpose :
+C Compute smoothing spline for smoothing parameter lambda
+C and compute one of three `criteria' (OCV , GCV , "df match").
+C See comments in ./sbart.f from which this is called
+
+ integer n,nk,icrit,ld4,ldnk,info
+ DOUBLE precision penalt,dofoff,x(n),y(n),w(n),ssw,
+ & knot(nk+4), coef(nk),sz(n),lev(n), crit, lambda,
+ * xwy(nk), hs0(nk),hs1(nk),hs2(nk),hs3(nk),
+ * sg0(nk),sg1(nk),sg2(nk),sg3(nk), abd(ld4,nk),
+ & p1ip(ld4,nk),p2ip(ldnk,nk)
+
+ EXTERNAL bvalue
+ double precision bvalue
+C local variables
+ double precision vnikx(4,1),work(16)
+ integer i,ileft,j,mflag, lenkno, ilo
+ double precision b0,b1,b2,b3,eps, xv,rss,df, sumw
+c
+c integer interv
+c external interv
+
+ lenkno = nk+4
+ ileft = 1
+ eps = 1d-11
+ ilo = 1
+
+C compute the coefficients coef() of estimated smooth
+
+ do 1 i=1,nk
+ coef(i) = xwy(i)
+ abd(4,i) = hs0(i)+lambda*sg0(i)
+ 1 continue
+
+ do 4 i=1,(nk-1)
+ abd(3,i+1) = hs1(i)+lambda*sg1(i)
+ 4 continue
+
+ do 6 i=1,(nk-2)
+ 6 abd(2,i+2) = hs2(i)+lambda*sg2(i)
+
+ do 8 i=1,(nk-3)
+ 8 abd(1,i+3) = hs3(i)+lambda*sg3(i)
+
+c factorize banded matrix abd:
+ call dpbfa(abd,ld4,nk,3,info)
+ if(info.ne.0) then
+C matrix could not be factorized -> ier := info
+ return
+ endif
+c solve linear system (from factorize abd):
+ call dpbsl(abd,ld4,nk,3,coef)
+
+C Value of smooth at the data points
+ do 12 i=1,n
+ xv = x(i)
+ 12 sz(i) = bvalue(knot,coef,nk,4,xv,0)
+
+C Compute the criterion function if requested
+
+ if(icrit .eq. 0)then
+ return
+ else
+C --- Ordinary or Generalized CV or "df match" ---
+
+C Get Leverages First
+ call sinerp(abd,ld4,nk,p1ip,p2ip,ldnk,0)
+ do 16 i=1,n
+ xv = x(i)
+ call interv(knot(1), nk+1, xv, ileft, mflag)
+ if(mflag .eq. -1) then
+ ileft = 4
+ xv = knot(4)+eps
+ else if(mflag .eq. 1) then
+ ileft = nk
+ xv = knot(nk+1) - eps
+ endif
+ j=ileft-3
+C call bspvd(knot,4,1,xv,ileft,4,vnikx,work)
+ call bsplvd(knot,lenkno,4,xv,ileft,work,vnikx,1)
+ b0=vnikx(1,1)
+ b1=vnikx(2,1)
+ b2=vnikx(3,1)
+ b3=vnikx(4,1)
+ lev(i) = (
+ & p1ip(4,j)*b0**2 + 2.d0*p1ip(3,j)*b0*b1 +
+ * 2.d0*p1ip(2,j)*b0*b2 + 2.d0*p1ip(1,j)*b0*b3 +
+ * p1ip(4,j+1)*b1**2 + 2.d0*p1ip(3,j+1)*b1*b2 +
+ * 2.d0*p1ip(2,j+1)*b1*b3 + p1ip(4,j+2)*b2**2 +
+ & 2.d0*p1ip(3,j+2)*b2*b3 + p1ip(4,j+3)*b3**2
+ & )*w(i)**2
+ 16 continue
+
+C Evaluate Criterion
+
+ if(icrit .eq. 1)then
+C Generalized CV
+ rss = ssw
+ df = 0d0
+ sumw = 0d0
+c w(i) are sqrt( wt[i] ) weights scaled in ../R/smspline.R such
+c that sumw = number of observations with w(i) > 0
+ do 24 i=1,n
+ rss = rss + ((y(i)-sz(i))*w(i))**2
+ df = df + lev(i)
+ sumw = sumw + w(i)**2
+ 24 continue
+
+ crit = (rss/sumw)/((1d0-(dofoff + penalt*df)/sumw)**2)
+c call dblepr("spar", 4, spar, 1)
+c call dblepr("crit", 4, crit, 1)
+
+ else if(icrit .eq. 2) then
+C Ordinary CV
+ crit = 0d0
+ do 30 i = 1,n
+ 30 crit = crit + (((y(i)-sz(i))*w(i))/(1-lev(i)))**2
+ crit = crit/n
+c call dblepr("spar", 4, spar, 1)
+c call dblepr("crit", 4, crit, 1)
+ else
+C df matching
+ crit = 0d0
+ do 32 i=1,n
+ 32 crit = crit+lev(i)
+ crit = 3 + (dofoff-crit)**2
+ endif
+ return
+ endif
+C Criterion evaluation
+ end
projects / mothur.git / blobdiff