c Part of R package KernSmooth c Copyright (C) 1995 M. P. Wand c c Unlimited use and distribution (see LICENCE). cccccccccc FORTRAN subroutine locpol.f cccccccccc c For computing an binned approximation to a c local bandwidth local polynomial kernel regression estimator c of an arbitrary derivative of a regression function. c LINPACK is used for matrix inversion. c Last changed: 10/02/95 subroutine locpol(xcnts,ycnts,idrv,delta,hdisc,Lvec,indic, + midpts,M,iQ,fkap,ipp,ippp,ss,tt,Smat,Tvec, + ipvt,cvest) integer i,j,k,ii,Lvec(*),M,iQ,mid,indic(*),midpts(*),ipvt(*), + info,idrv,ipp,ippp,indss double precision xcnts(*),ycnts(*),fkap(*),hdisc(*), + cvest(*),delta,ss(M,ippp),tt(M,ipp), + Smat(ipp,ipp),Tvec(ipp),fac c Obtain kernel weights mid = Lvec(1) + 1 do 10 i=1,(iQ-1) midpts(i) = mid fkap(mid) = 1.0d0 do 20 j=1,Lvec(i) fkap(mid+j) = exp(-(delta*j/hdisc(i))**2/2) fkap(mid-j) = fkap(mid+j) 20 continue mid = mid + Lvec(i) + Lvec(i+1) + 1 10 continue midpts(iQ) = mid fkap(mid) = 1.0d0 do 30 j=1,Lvec(iQ) fkap(mid+j) = exp(-(delta*j/hdisc(iQ))**2/2) fkap(mid-j) = fkap(mid+j) 30 continue c Combine kernel weights and grid counts do 40 k = 1,M if (xcnts(k).ne.0) then do 50 i = 1,iQ do 60 j = max(1,k-Lvec(i)),min(M,k+Lvec(i)) if (indic(j).eq.i) then fac = 1.0d0 ss(j,1) = ss(j,1) + xcnts(k)*fkap(k-j+midpts(i)) tt(j,1) = tt(j,1) + ycnts(k)*fkap(k-j+midpts(i)) do 70 ii = 2,ippp fac = fac*delta*(k-j) ss(j,ii) = ss(j,ii) + + xcnts(k)*fkap(k-j+midpts(i))*fac if (ii.le.ipp) then tt(j,ii) = tt(j,ii) + + ycnts(k)*fkap(k-j+midpts(i))*fac endif 70 continue endif 60 continue 50 continue endif 40 continue do 80 k = 1,M do 90 i = 1,ipp do 100 j = 1,ipp indss = i + j - 1 Smat(i,j) = ss(k,indss) 100 continue Tvec(i) = tt(k,i) 90 continue call dgefa(Smat,ipp,ipp,ipvt,info) call dgesl(Smat,ipp,ipp,ipvt,Tvec,0) cvest(k) = Tvec(idrv+1) 80 continue return end cccccccccc End of locpol.f cccccccccc