[Rcpp-devel] Best Practice for Optimize Functions in RCPP

[Avraham Adler]

Hello, Simon.

I ran into a similar problem before (with uniroot
<https://stat.ethz.ch/R-manual/R-devel/library/stats/html/uniroot.html>),
and what I found was that the function in R is actually written in C. I
found the original code, but not being a real programmer, I stopped working
on what I was doing and put it off until the point where I have enough time
to develop the skill to port that into RCpp (maybe 2047?). In your
case, optimize()
<https://stat.ethz.ch/R-manual/R-devel/library/stats/html/optimize.html>itself
is a translation of an algorithm by Brent in FORTRAN which can be found here
(textfile) <http://www.netlib.org/fmm/fmin.f>. Perhaps you can translate it
into C++ and call it directly?

Avi

On Tue, Dec 23, 2014 at 12:04 AM, Simon Riddell <simonruw at gmail.com> wrote:

> Hello,
>
> I have been judiciously using RCPP for six months, and have had my
> numerous questions answered so far from previous threads. I have now run
> into an issue I cannot get a handle on:
>
> I have converted a fairly large (recursive) Kalman filter function from R
> to C++ using RCPP. This function is then called within the R optim()
> function, subject to constraints, which estimates a set of ~30 parameters.
>
> My issue occurs within the C++ Kalman Filter function, where, I use the
> optimize() function to calculate the yield to maturity rate of various
> bonds. I do this by calling back to the R environment to access the
> optimize() function. Below is the R Function I create to be used within the
> Kalman filter, and below this R function is my method for calling it within
> the C++ code. To complicate matters further, the R Function calls a C++
> Function. To clarify: The Kalman Filter C++ code calls an R function, and
> this R Function calls an additional separate C++ function. (Code included
> below)
>
> As I iterate the Kalman filter it runs perfectly for anywhere from 30
> minutes to six hours (and produces correct output when matched to the R
> code), but it inevitably crashes. From past reading I have done, Dirk has
> before mentioned that calling an R function many times within C++ is
> usually not a good idea. As a result I suspect this is my issue (the error
> codes vary, sometimes mentioning numerical errors, other times recursive
> errors, other times random RCPP error codes -- I can document and provide
> them if needed)
>
> My biggest impasse is I cannot figure out a way to complete this without
> calling the R optimize() function, and cannot find any RCPP optimize
> functions to use instead. Thank you for reading.
>
>
> *R Function (**IRNPV.CPP is the C++ function, which R optimizes the rate
> parameter over):*
>
> optimcpp<-function(CoupDate=1,coupNo=1,coup=1,price=1,rate=1)
> {
> m<-optimize(function(CoupDate,coupNo,coup,price,rate) *IRNPV.CPP*
> (CoupDate=CoupDate,coupNo=coupNo,coup=coup,*rate*
> )-price)^2,c(-0.05,0.2),tol=1e-20,CoupDate=CoupDate,coupNo=coupNo,coup=coup,price=price)
> m$minimum
> }
>
> *Accessing the R environment within the C++ code:*
> CPP.SRC <- '
> using namespace arma;
> Rcpp::Environment global = Rcpp::Environment::global_env();
> Function optimizecpp = global["optimcpp"];
> //Various matrix computations to calculate CD, CN, Co, & Pricex[0]
> optimvec0 = optimizecpp(CD,CN,Co,pricex[0],Ra);
> '
>
> *IRNPV.CPP Function *(What the R Optimize() function optimizes 'rate'
> over -- *Very* *Likely Unnecessary for Purposes of this Question)*
>
> IR.NPV.TIPS.CBF.SRC <- '
> using namespace arma;
>
> double CD = Rcpp::as<double>(CoupDate);
> double CN = Rcpp::as<double>(coupNo);
> double RN = Rcpp::as<double>(rate);
> double Co = Rcpp::as<double>(coup);
>
> Rcpp::NumericVector LM;
> mat DiscountFunc;
> double length;
>
> double price;
>
> if (CN > 1) {
>
> length = floor((((CD+0.5*(CN-1))-CD)/0.50))+1;
>
> for (double i = CD; i <= (CD+0.5*(CN-1))+.05; i += 0.5) {
> LM.insert(LM.end(),i);
> }
>
> DiscountFunc.set_size(LM.size(), 1);
> DiscountFunc.fill(0);
>
>
> double k = 0;
> mat::row_iterator q = DiscountFunc.begin_row(0);
> mat::row_iterator w = DiscountFunc.end_row((LM.size()-1));
> for(mat::row_iterator i=q; i!=w; ++i)
>      {
>      (*i) = exp(-RN*LM[k]);
>      k = k + 1;
>      }
>
> price = CD*Co*DiscountFunc[0];
>
> for (int i=1; i<(LM.size()); ++i) {
> price = price+0.5*Co*DiscountFunc[i];
> }
>
>
> }
> else {
> double DiscountFunc;
> DiscountFunc = exp(-RN*CD);
> price = (1+CD*Co)*DiscountFunc;
> }
> return Rcpp::wrap(price);
>
> '
>
>
> IRNPV.CPP <- cxxfunction(signature(CoupDate="NumericVector",
> coupNo="NumericVector", coup="NumericVector",rate="NumericVector"),
> IR.NPV.TIPS.CBF.SRC, include=CMATH, plugin="RcppArmadillo")
>
>
>
> Thank you,
> Simon
>
>
> --
> Simon Alexander Riddell
> Economic Research RA
> Federal Reserve Bank
>
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