Displaying 5 results from an estimated 5 matches for "naivesum".
2019 Feb 19
4
code for sum function
The algorithm does make a differece. You can use Kahan's summation
algorithm (https://en.wikipedia.org/wiki/Kahan_summation_algorithm) to
reduce the error compared to the naive summation algorithm. E.g., in R
code:
naiveSum <-
function(x) {
s <- 0.0
for(xi in x) s <- s + xi
s
}
kahanSum <- function (x)
{
s <- 0.0
c <- 0.0 # running compensation for lost low-order bits
for(xi in x) {
y <- xi - c
t <- s + y # low-order bits of y may be lost here
c <- (t - s)...
2019 Feb 20
0
code for sum function
...William Dunlap <wdunlap at tibco.com wrote:
> The algorithm does make a differece. You can use Kahan's summation
> algorithm (https://en.wikipedia.org/wiki/Kahan_summation_algorithm) to
> reduce the error compared to the naive summation algorithm. E.g., in R
> code:
>
> naiveSum <-
> function(x) {
> s <- 0.0
> for(xi in x) s <- s + xi
> s
> }
> kahanSum <- function (x)
> {
> s <- 0.0
> c <- 0.0 # running compensation for lost low-order bits
> for(xi in x) {
> y <- xi - c
> t <- s + y...
2019 Feb 19
0
code for sum function
...19 2:08 p.m., William Dunlap via R-devel wrote:
> The algorithm does make a differece. You can use Kahan's summation
> algorithm (https://en.wikipedia.org/wiki/Kahan_summation_algorithm) to
> reduce the error compared to the naive summation algorithm. E.g., in R
> code:
>
> naiveSum <-
> function(x) {
> s <- 0.0
> for(xi in x) s <- s + xi
> s
> }
> kahanSum <- function (x)
> {
> s <- 0.0
> c <- 0.0 # running compensation for lost low-order bits
> for(xi in x) {
> y <- xi - c
> t <- s + y...
2019 Feb 20
0
code for sum function
...at tibco.com wrote:
>
>> The algorithm does make a differece. You can use Kahan's summation
>> algorithm (https://en.wikipedia.org/wiki/Kahan_summation_algorithm) to
>> reduce the error compared to the naive summation algorithm. E.g., in R
>> code:
>>
>> naiveSum <-
>> function(x) {
>> s <- 0.0
>> for(xi in x) s <- s + xi
>> s
>> }
>> kahanSum <- function (x)
>> {
>> s <- 0.0
>> c <- 0.0 # running compensation for lost low-order bits
>> for(xi in x) {
>>...
2019 Feb 14
5
code for sum function
Hello,
I am trying to write FORTRAN code to do the same as some R code I have.
I get (small) differences when using the sum function in R. I know there
are numerical routines to improve precision, but I have not been able to
figure out what algorithm R is using. Does anyone know this? Or where
can I find the code for the sum function?
Regards,
Rampal Etienne