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

[Simon Riddell]

Brief Update,

Avraham's advice helped me get a better idea of where to start. What I am
now trying to do is learn from this post, which explains how to use
external libraries in RCPP (
http://stackoverflow.com/questions/13995266/using-3rd-party-header-files-with-rcpp).
And secondly, try to use that to implement this optimize function (
http://www.boost.org/doc/libs/1_57_0/libs/math/doc/html/math_toolkit/internals1/minima.html
).

If anyone has additional links or input I would be grateful to receive it,
I do not expect anyone to hold my hand through this.

Thank you again for your time and help,
Simon

On Mon, Dec 22, 2014 at 9:25 PM, Avraham Adler <avraham.adler at gmail.com>
wrote:

> 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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>> Rcpp-devel at lists.r-forge.r-project.org
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>>
>
>


-- 
Simon Alexander Riddell
London School of Economics
linkedin.com/in/simonriddell <http://uk.linkedin.com/in/simonriddell>
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