Thanks! I'll use if(rcf <= std::numeric_limits<double>::epsilon()) instead
of rcf==0.
On Fri, Jan 28, 2022 at 7:32 PM Dirk Eddelbuettel <e...@debian.org> wrote:
>
> On 28 January 2022 at 13:25, Alex Ilich wrote:
> | Thank you Neal and Dirk. Based on these comments I think using
> arma::rcond
>
> Ah, yes, of course. Should have remembered arma::rcond.
>
> | to get the reciprocal of the condition factor, and checking if that is
> zero
> | rather than the determinant may be the route to go. At least for this
> | example that works.
> |
> | library(Rcpp)
> |
> | cppFunction(depends="RcppArmadillo", "NumericVector C_OLS(arma::mat X,
> | arma::mat Y){
> | arma::mat Xt = trans(X);
> | arma::mat XtX = Xt * X;
> | double rcf = rcond(XtX);
> | Rcout << rcf; //print reciprocal of condition factor
> | if(rcf==0){
>
> Re-read Neal's first email. You probably do not want zero (apart from all
> the R FAQ 7.31 reasons to not compare a double with equality :wink: )
>
> Dirk
>
> | NumericVector B2(X.n_cols, NA_REAL);
> | return B2;
> | } else{
> | arma::mat XtX_inv= inv(XtX);
> | NumericVector B = Rcpp::as<Rcpp::NumericVector>(wrap(XtX_inv * (Xt *
> | Y)));
> | return B;
> | }}")
> |
> | X<- matrix(data=c(-250, -250, -250, -250, -250, -250, 250, 200, 150,
> | 100, 50, 0, 1, 1, 1, 1, 1, 1), ncol=3, nrow=6)
> |
> |
> | X2<- X
> |
> | X2[1,2]<- X[1,2] + 5.684342e-14 #Add a slight numeric precision issue
> |
> | Y<- matrix(1:6, ncol=1)
> |
> | C_OLS(X,Y)
> | # 0[1] NA NA NA
> |
> | C_OLS(X2,Y)
> | # 0[1] NA NA NA
> |
> |
> |
> | On Fri, Jan 28, 2022 at 11:53 AM Alex Ilich <alexilic...@gmail.com>
> wrote:
> |
> | > Hi, I have some code I've written to calculate regression parameters
> using
> | > ordinarily least squares using RcppArmadillo. This is meant to be
> performed
> | > iteratively over many small subsets (sliding window over spatial raster
> | > data) so I'd like to automatically detect when the regression can't be
> | > performed and just return a vector of NA's. Currently I check to see
> if the
> | > determinant is 0 in order to see if the XtX matrix can be inverted and
> it
> | > seems to work in the vast majority of cases but I did run into a case
> where
> | > a small amount of precision error was introduced and for some reason
> this
> | > causes the determinant to be non-zero in C++ however, the matrix still
> is
> | > considered singular (uninvertible) leading to an error. I was
> wondering if
> | > anyone had any suggestions? Maybe there's a minimum value non-zero
> value
> | > where it's considered essentially singular that I could use instead of
> 0,
> | > or maybe there's a way to return a vector of NAs if an error is
> detected
> | > rather than stopping execution and printing an error message. I've also
> | > seen that pinv can be used, but from some tests I ran it's
> substantially
> | > slower, so I'd like to avoid using that. I've included some example
> code
> | > below. Any suggestions would be greatly appreciated.
> | >
> | > Thanks,
> | > Alex
> | >
> | > library(Rcpp)
> | > cppFunction(depends="RcppArmadillo", "NumericVector C_OLS(arma::mat X,
> | > arma::mat Y){
> | > arma::mat Xt = trans(X);
> | > arma::mat XtX = Xt * X;
> | > double d = det(XtX);
> | > Rcout << d; //print determinant
> | > if(d==0){
> | > NumericVector B2(X.n_cols, NA_REAL);
> | > return B2;
> | > } else{
> | > arma::mat XtX_inv= inv(XtX);
> | > NumericVector B = Rcpp::as<Rcpp::NumericVector>(wrap(XtX_inv * (Xt
> *
> | > Y)));
> | > return B;
> | > }}")
> | >
> | > X<- matrix(data=c(-250, -250, -250, -250, -250, -250, 250, 200, 150,
> | > 100, 50, 0, 1, 1, 1, 1, 1, 1), ncol=3, nrow=6)
> | >
> | >
> | > X2<- X
> | >
> | > X2[1,2]<- X[1,2] + 5.684342e-14 #Add a slight numeric precision issue
> | >
> | > Y<- matrix(1:6, ncol=1)
> | >
> | > #Determinant of XtX in R is 0 for both
> | > det(t(X) %*% X) ==0 #TRUE
> | > det(t(X2) %*% X2) ==0 #TRUE
> | >
> | > C_OLS(X,Y) #Determinant is 0 in C++ and correctly returns a vector of
> NA's
> | > #0[1] NA NA NA
> | >
> | > C_OLS(X2,Y) #Determinant is not 0 in C++ so the if statement is not
> | > triggered but the matrix is still uninvertible
> | > # 4.57764e-05
> | > # error: inv(): matrix is singular
> | > # Error in C_OLS(X2, Y) : inv(): matrix is singular
> | >
> | _______________________________________________
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> --
> https://dirk.eddelbuettel.com | @eddelbuettel | e...@debian.org
>
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