search for: convolved

Hi, Man page for 'convolve' says: conj: logical; if 'TRUE', take the complex _conjugate_ before back-transforming (default, and used for usual convolution). The complex conjugate of 'x', of 'y', of both? In fact it seems that it takes the complex conjugate of 'y' only which is OK but might be worth mentioning because (1) conj=TRUE is the

Dear R People: Here is something that I am sure is very simple. I'm just trying to re-create the C convolution example in the Extensions manual. Here is the subroutine: void convolve(double *a, int *na, double *b, int *nb, double *ab) { R_len_t i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++) ab[i] = 0.0; for(i = 0; i < *na; i++) for(j = 0; j < *nb; j++) ab[i + j] += a[i] *

...gt; > > > and just for historical fun here's the help file in that > > cute olde help file format: > > > > TITLE(convolve @ Fast Convolution) > > USAGE( > > convolve(a, b, conj=false) > > ) > > ARGUMENTS( > > ARG(a,b @ the sequences to be convolved.) > > ARG(conj @ logical, if true the transform of LANG(b) is conjugated > > before back-transformation.) > > ) > > DESCRIPTION( > > LANG(convolve) uses the Fast Fourier Transform to compute the > > convolution of the sequences given as its arguments. > > P...

We obtained some disturbing results from convolve() (inaccuracies and negative probabilities). We'll try to make the context clear in as few lines as possible... Our function panjer() (code below) basically computes recursively the probability mass function of a compound Poisson distribution. When the Poisson parameter lambda is very large, the starting value of the recursive scheme ---

Dear R users, I want to call C code via the .C or .Call interface. This works fine with integer values but using doubles the array received in C will be set to zeros. I have tried the convolve examples (Writing R extensions, chapter 5.2) and still the resulting array consists of zeros. My code (shortened for my purposes. Original did not work either):

Hi, the function stats::convolve does not mention efficient usage of the underlying FFT algorithm, such as (a) if type="circular", then length(x)=length(y) should have many factors (e.g. length(x) = length(y) = 2^n) (b) if type="open" or "filter", then length(x)+length(y)-1 should have many factors (e.g. length(x)+length(y)-1 = 2^n) In particular the latter may

I have been experimenting with convolve(). What I know about convolution I learned from engineering (they call this stuff linear systems theory), not statistics, so maybe this is all just a matter of different conventions. BUT I notice very weird things with convolve(). 1. First example, from the classic Bracewell The Fourier transform and its applications, chap 3 (p.32 in 2nd edition): {2 2 3 3

This patch supplies software IEEE floating point support. The comment from the patch reproduced below says all there is to say. This patch contains the prior "cleanup" patch; please don't apply that one. Please let me know of any bugs. It is tested reasonably well, but until I put together random tests it's hard to have 100% confidence. Neil. /* A self-contained host- and

Hi, I'm new to R, and I'm a bit confused with the "convolve()" function. If I do: x<-c(1, 2, 3) convolve(x, rev(x), TRUE, "open") = 9 12 10 4 1 But I expected: 3 8 14 8 3 (like in Octave/MATLAB - conv(x, reverse(x)) ) 3 2 1 x 1 2 3 = 3 2 1 0 6 4 2 0 0 9 6 3 = 3 8 14 8 3 The thing is, that "convolve(x, x, TRUE, "open")" works. For me

Dear R-ophiles, I've found something very odd when I apply convolve to ever larger vectors. Here is an example below with vectors ranging from 2^11 to 2^17. There is a funny bump up at 2^12. Then it gets very slow at 2^16. > for( i in 11:20 )print( system.time(convolve(1:2^i,1:2^i,type="o"))) user system elapsed 0.002 0.000 0.002 user system elapsed 0.373

Hi, I compiled a C program file on Borland C++ 5.5 compiler to get one dll output (as instructed in the file readme.package). The C program file is just the example on page 31 of "writing R extensions": void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++) ab[i] = 0.0; for(i = 0; i < *na; i++) for(j = 0; j

Hi everyone! I'm trying to lear how to call external C code in R but even the R help web-page example is drive me crazy. I copy-paste the example at: http://stat.ethz.ch/R-manual/R-patched/doc/manual/R-exts.html#Interface%20functions%20.C%20and%20.Fortran here is the example: void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0;

Dear all, I have an image that I need to filter, and so I'm looking for a method to convolve it with a matrix. If I understood the docs for convolve correctly, it only works in 1D (and I have tried to convolve, it didn't look good). So, I wondered if anybody have implemented 2D convolution in R, or have any good advices to share (beyond having a look at mvfft), before I go hacking?

Hi, I am hoping some one can help me. I am learning to use C and would like to learn how to call c code in R. I have look at Writing R Extensions and I tried to copy the example on page 38 void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++) ab[i] = 0.0; for(i = 0; i < *na; i++) for(j = 0; j <

Hi, I am happy to announce that I finished the translation of almost all LGPL'ed R headerfiles to Delphi. As a test I did several demos which basically contain delphized versions of all the examples of chapter 5 in "Writing R Extensions". Please have a look in the attachments for details (DemosAndHeaders.txt), more information (Readme.txt) and an example of how it looks

Dear all, I'm studing how to include .c code in my .r functions . In the R-exts.pdf manual I have found the following code. At one point the author write "called from R by"... How can I load a .c file on R? ( I am using a xp windows as so.) Thank you ale void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++)

Hi all, i have some problem in using shared objects. I tried the example found in "Writing R Extension", pg. 33 I used the .c file prova.c : ------------------------------------------------------------------- #include <R.h> #include <Rinternals.h> void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j , nab = *na + *nb - 1; for (i = 0; i < nab;

I want to generate the following outcome using convolution of two sequences. x <- c(1,2,3,4,5) y <- c(6,7,8,9) The resulting convolution vector is 6 19 40 70 100 94 76 45 When using convolve(), it is hard to produce the result above. Would you help me out to get that? Best regards Moohwan Kim

Jeff Brown wrote: > > Hi, > > I'm trying to learn to use .C, which lets one invoke compiled C code from > within R. To do that, one has to first get the C code into R as a shared > object, which (I think) means first compiling it (with COMPILE or SHLIB) > and then loading it (with dyn.load()). > I would suggest taking it a step further and building an R package

I have received a few private emails asking for some simple demonstration of calling Java code from R using the rJava package (which can be installed directly inside R). Here is one example for convolving two vectors (an example in the R manual about linking C with R). First write a Java program public class my_convolve { public static double[] convolve(double[] a, double[] b)