Marc Schwartz
2016-Jun-29 18:06 UTC
[R] Understanding and predict round-off errors sign on simple functions
Hi, Just to augment Bert's comments, I presume that you are aware of the relevant R FAQ: https://cran.r-project.org/doc/FAQ/R-FAQ.html#Why-doesn_0027t-R-think-these-numbers-are-equal_003f That you had an expectation of the difference being 0 suggested to me that you might not be, but my apologies if that is not the case. That being said, there are some higher precision CRAN packages that may offer some additional functionality, with the potential limitations that Bert references below. More information is available in the Numerical Mathematics CRAN Task View: https://cran.r-project.org/web/views/NumericalMathematics.html In addition, with the caveat that I have not used it, there is the 'propagate' package on CRAN that may be relevant to what you want to be able to anticipate, at some level: https://cran.r-project.org/web/packages/propagate/index.html It has not been updated in a while and there are some notes for the CRAN package checks, that suggest that the maintainer may not be active at this point. Regards, Marc> On Jun 29, 2016, at 10:13 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > I am certainly no expert, but I would assume that: > > 1. Roundoff errors depend on the exact numerical libraries and > versions that are used, and so general language comparisons are > impossible without that information; > > 2. Roundoff errors depend on the exact calculations being done and > machine precision and are very complicated to determine > > So I would say the answer to your questions is no. > > But you should probably address such a question to a numerical analyst > for an authoritative answer. Maybe try stats.stackexchange.com . > > -- Bert > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along > and sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > On Wed, Jun 29, 2016 at 2:55 AM, Sirhc via R-help <r-help at r-project.org> wrote: >> Hi, >> >> >> >> May be it is a basic thing but I would like to know if we can anticipate >> round-off errors sign. >> >> >> >> Here is an example : >> >> >> >> # numerical matrix >> >> m <- matrix(data=cbind(rnorm(10, 0), rnorm(10, 2), rnorm(10, 5)), nrow=10, >> ncol=3) >> >> >> >>> m >> >> [,1] [,2] [,3] >> >> [1,] 0.4816247 1.1973502 3.855641 >> >> [2,] -1.2174937 0.7356427 4.393279 >> >> [3,] 0.8504074 2.5286509 2.689196 >> >> [4,] 1.8048642 1.8580804 6.665237 >> >> [5,] -0.6749397 1.0944277 4.838608 >> >> [6,] 0.8252034 1.5595268 3.681695 >> >> [7,] 1.3002208 0.9582693 4.561577 >> >> [8,] 1.6950923 3.5677921 6.005078 >> >> [9,] 0.6509285 0.9025964 5.082288 >> >> [10,] -0.5676040 1.3281102 4.446451 >> >> >> >> #weird moving average of period 1 ! >> >> mma <- apply(m, 2, SMA, n=1) >> >> >> >>> mma >> >> [,1] [,2] [,3] >> >> [1,] NA NA NA >> >> [2,] -1.2174937 0.7356427 4.393279 >> >> [3,] 0.8504074 2.5286509 2.689196 >> >> [4,] 1.8048642 1.8580804 6.665237 >> >> [5,] -0.6749397 1.0944277 4.838608 >> >> [6,] 0.8252034 1.5595268 3.681695 >> >> [7,] 1.3002208 0.9582693 4.561577 >> >> [8,] 1.6950923 3.5677921 6.005078 >> >> [9,] 0.6509285 0.9025964 5.082288 >> >> [10,] -0.5676040 1.3281102 4.446451 >> >> >> >> >> >> #difference should be 0 but here is the result >> >>> m - mma >> >> [,1] [,2] [,3] >> >> [1,] NA NA NA >> >> [2,] 0.000000e+00 0.000000e+00 -8.881784e-16 >> >> [3,] 0.000000e+00 0.000000e+00 -8.881784e-16 >> >> [4,] 0.000000e+00 4.440892e-16 -8.881784e-16 >> >> [5,] -1.110223e-16 4.440892e-16 -8.881784e-16 >> >> [6,] -1.110223e-16 2.220446e-16 -4.440892e-16 >> >> [7,] -2.220446e-16 2.220446e-16 0.000000e+00 >> >> [8,] -2.220446e-16 0.000000e+00 0.000000e+00 >> >> [9,] -3.330669e-16 2.220446e-16 -8.881784e-16 >> >> [10,] -3.330669e-16 4.440892e-16 -8.881784e-16 >> >> >> >> SMA function use runMean >> >> # TTR / R / MovingAverages.R >> >> "SMA" <- function(x, n=10, ...) { # Simple Moving Average >> >> ma <- runMean( x, n ) >> >> if(!is.null(dim(ma))) { >> >> colnames(ma) <- "SMA" >> >> } >> >> return(ma) >> >> } >> >> >> >> >> >> Can anyone explain me that round error type? >> >> Is it possible to reproduce this same error generation in another language >> like C++ or C# ? >> >> >> >> Thanks in advance for your answers >> >> >> >> Regards >> >> >> >> Chris
DIGHE, NILESH [AG/2362]
2016-Jun-30 12:02 UTC
[R] Understanding and predict round-off errors sign on simple functions
Using "runmean" function from caTools package within your SMA function appears to solve the issue. Please see details below. library(caTools)> dput(m)structure(c(-0.626453810742332, 0.183643324222082, -0.835628612410047, 1.59528080213779, 0.329507771815361, -0.820468384118015, 0.487429052428485, 0.738324705129217, 0.575781351653492, -0.305388387156356, 3.51178116845085, 2.38984323641143, 1.3787594194582, -0.2146998871775, 3.12493091814311, 1.95506639098477, 1.98380973690105, 2.9438362106853, 2.82122119509809, 2.59390132121751, 5.91897737160822, 5.78213630073107, 5.07456498336519, 3.01064830413663, 5.61982574789471, 4.943871260471, 4.84420449329467, 3.52924761610073, 4.52184994489138, 5.4179415601997), .Dim = c(10L, 3L))> dput(SMA)function (x, n = 10, ...) { ma <- runmean(x, n) if (!is.null(dim(ma))) { colnames(ma) <- "SMA" } return(ma) } mma <- apply(m, 2, SMA, n=1) results<-mma-m> dput(results)structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 3L)) Nilesh -----Original Message----- From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Marc Schwartz Sent: Wednesday, June 29, 2016 1:07 PM To: Bert Gunter Cc: R-help Subject: Re: [R] Understanding and predict round-off errors sign on simple functions Hi, Just to augment Bert's comments, I presume that you are aware of the relevant R FAQ: https://cran.r-project.org/doc/FAQ/R-FAQ.html#Why-doesn_0027t-R-think-these-numbers-are-equal_003f That you had an expectation of the difference being 0 suggested to me that you might not be, but my apologies if that is not the case. That being said, there are some higher precision CRAN packages that may offer some additional functionality, with the potential limitations that Bert references below. More information is available in the Numerical Mathematics CRAN Task View: https://cran.r-project.org/web/views/NumericalMathematics.html In addition, with the caveat that I have not used it, there is the 'propagate' package on CRAN that may be relevant to what you want to be able to anticipate, at some level: https://cran.r-project.org/web/packages/propagate/index.html It has not been updated in a while and there are some notes for the CRAN package checks, that suggest that the maintainer may not be active at this point. Regards, Marc> On Jun 29, 2016, at 10:13 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > I am certainly no expert, but I would assume that: > > 1. Roundoff errors depend on the exact numerical libraries and > versions that are used, and so general language comparisons are > impossible without that information; > > 2. Roundoff errors depend on the exact calculations being done and > machine precision and are very complicated to determine > > So I would say the answer to your questions is no. > > But you should probably address such a question to a numerical analyst > for an authoritative answer. Maybe try stats.stackexchange.com . > > -- Bert > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along > and sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > On Wed, Jun 29, 2016 at 2:55 AM, Sirhc via R-help <r-help at r-project.org> wrote: >> Hi, >> >> >> >> May be it is a basic thing but I would like to know if we can >> anticipate round-off errors sign. >> >> >> >> Here is an example : >> >> >> >> # numerical matrix >> >> m <- matrix(data=cbind(rnorm(10, 0), rnorm(10, 2), rnorm(10, 5)), >> nrow=10, >> ncol=3) >> >> >> >>> m >> >> [,1] [,2] [,3] >> >> [1,] 0.4816247 1.1973502 3.855641 >> >> [2,] -1.2174937 0.7356427 4.393279 >> >> [3,] 0.8504074 2.5286509 2.689196 >> >> [4,] 1.8048642 1.8580804 6.665237 >> >> [5,] -0.6749397 1.0944277 4.838608 >> >> [6,] 0.8252034 1.5595268 3.681695 >> >> [7,] 1.3002208 0.9582693 4.561577 >> >> [8,] 1.6950923 3.5677921 6.005078 >> >> [9,] 0.6509285 0.9025964 5.082288 >> >> [10,] -0.5676040 1.3281102 4.446451 >> >> >> >> #weird moving average of period 1 ! >> >> mma <- apply(m, 2, SMA, n=1) >> >> >> >>> mma >> >> [,1] [,2] [,3] >> >> [1,] NA NA NA >> >> [2,] -1.2174937 0.7356427 4.393279 >> >> [3,] 0.8504074 2.5286509 2.689196 >> >> [4,] 1.8048642 1.8580804 6.665237 >> >> [5,] -0.6749397 1.0944277 4.838608 >> >> [6,] 0.8252034 1.5595268 3.681695 >> >> [7,] 1.3002208 0.9582693 4.561577 >> >> [8,] 1.6950923 3.5677921 6.005078 >> >> [9,] 0.6509285 0.9025964 5.082288 >> >> [10,] -0.5676040 1.3281102 4.446451 >> >> >> >> >> >> #difference should be 0 but here is the result >> >>> m - mma >> >> [,1] [,2] [,3] >> >> [1,] NA NA NA >> >> [2,] 0.000000e+00 0.000000e+00 -8.881784e-16 >> >> [3,] 0.000000e+00 0.000000e+00 -8.881784e-16 >> >> [4,] 0.000000e+00 4.440892e-16 -8.881784e-16 >> >> [5,] -1.110223e-16 4.440892e-16 -8.881784e-16 >> >> [6,] -1.110223e-16 2.220446e-16 -4.440892e-16 >> >> [7,] -2.220446e-16 2.220446e-16 0.000000e+00 >> >> [8,] -2.220446e-16 0.000000e+00 0.000000e+00 >> >> [9,] -3.330669e-16 2.220446e-16 -8.881784e-16 >> >> [10,] -3.330669e-16 4.440892e-16 -8.881784e-16 >> >> >> >> SMA function use runMean >> >> # TTR / R / MovingAverages.R >> >> "SMA" <- function(x, n=10, ...) { # Simple Moving Average >> >> ma <- runMean( x, n ) >> >> if(!is.null(dim(ma))) { >> >> colnames(ma) <- "SMA" >> >> } >> >> return(ma) >> >> } >> >> >> >> >> >> Can anyone explain me that round error type? >> >> Is it possible to reproduce this same error generation in another >> language like C++ or C# ? >> >> >> >> Thanks in advance for your answers >> >> >> >> Regards >> >> >> >> Chris______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. This email and any attachments were sent from a Monsanto email account and may contain confidential and/or privileged information. If you are not the intended recipient, please contact the sender and delete this email and any attachments immediately. Any unauthorized use, including disclosing, printing, storing, copying or distributing this email, is prohibited. All emails and attachments sent to or from Monsanto email accounts may be subject to monitoring, reading, and archiving by Monsanto, including its affiliates and subsidiaries, as permitted by applicable law. Thank you.
c.jallet at laposte.net
2016-Jul-01 07:10 UTC
[R] Understanding and predict round-off errors sign on simple functions
Thank you for all your answers and I will take a look to the 'propagate' package. Ps: first time I am participating to a mailing list, I hope I answer to the right emails. -----Original Message----- From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of DIGHE, NILESH [AG/2362] Sent: jeudi, 30 juin 2016 14:02 To: Marc Schwartz <marc_schwartz at me.com>; Bert Gunter <bgunter.4567 at gmail.com> Cc: R-help <r-help at r-project.org> Subject: Re: [R] Understanding and predict round-off errors sign on simple functions Using "runmean" function from caTools package within your SMA function appears to solve the issue. Please see details below. library(caTools)> dput(m)structure(c(-0.626453810742332, 0.183643324222082, -0.835628612410047, 1.59528080213779, 0.329507771815361, -0.820468384118015, 0.487429052428485, 0.738324705129217, 0.575781351653492, -0.305388387156356, 3.51178116845085, 2.38984323641143, 1.3787594194582, -0.2146998871775, 3.12493091814311, 1.95506639098477, 1.98380973690105, 2.9438362106853, 2.82122119509809, 2.59390132121751, 5.91897737160822, 5.78213630073107, 5.07456498336519, 3.01064830413663, 5.61982574789471, 4.943871260471, 4.84420449329467, 3.52924761610073, 4.52184994489138, 5.4179415601997), .Dim = c(10L, 3L))> dput(SMA)function (x, n = 10, ...) { ma <- runmean(x, n) if (!is.null(dim(ma))) { colnames(ma) <- "SMA" } return(ma) } mma <- apply(m, 2, SMA, n=1) results<-mma-m> dput(results)structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 3L)) Nilesh -----Original Message----- From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Marc Schwartz Sent: Wednesday, June 29, 2016 1:07 PM To: Bert Gunter Cc: R-help Subject: Re: [R] Understanding and predict round-off errors sign on simple functions Hi, Just to augment Bert's comments, I presume that you are aware of the relevant R FAQ: https://cran.r-project.org/doc/FAQ/R-FAQ.html#Why-doesn_0027t-R-think-these- numbers-are-equal_003f That you had an expectation of the difference being 0 suggested to me that you might not be, but my apologies if that is not the case. That being said, there are some higher precision CRAN packages that may offer some additional functionality, with the potential limitations that Bert references below. More information is available in the Numerical Mathematics CRAN Task View: https://cran.r-project.org/web/views/NumericalMathematics.html In addition, with the caveat that I have not used it, there is the 'propagate' package on CRAN that may be relevant to what you want to be able to anticipate, at some level: https://cran.r-project.org/web/packages/propagate/index.html It has not been updated in a while and there are some notes for the CRAN package checks, that suggest that the maintainer may not be active at this point. Regards, Marc> On Jun 29, 2016, at 10:13 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > I am certainly no expert, but I would assume that: > > 1. Roundoff errors depend on the exact numerical libraries and > versions that are used, and so general language comparisons are > impossible without that information; > > 2. Roundoff errors depend on the exact calculations being done and > machine precision and are very complicated to determine > > So I would say the answer to your questions is no. > > But you should probably address such a question to a numerical analyst > for an authoritative answer. Maybe try stats.stackexchange.com . > > -- Bert > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along > and sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > On Wed, Jun 29, 2016 at 2:55 AM, Sirhc via R-help <r-help at r-project.org>wrote:>> Hi, >> >> >> >> May be it is a basic thing but I would like to know if we can >> anticipate round-off errors sign. >> >> >> >> Here is an example : >> >> >> >> # numerical matrix >> >> m <- matrix(data=cbind(rnorm(10, 0), rnorm(10, 2), rnorm(10, 5)), >> nrow=10, >> ncol=3) >> >> >> >>> m >> >> [,1] [,2] [,3] >> >> [1,] 0.4816247 1.1973502 3.855641 >> >> [2,] -1.2174937 0.7356427 4.393279 >> >> [3,] 0.8504074 2.5286509 2.689196 >> >> [4,] 1.8048642 1.8580804 6.665237 >> >> [5,] -0.6749397 1.0944277 4.838608 >> >> [6,] 0.8252034 1.5595268 3.681695 >> >> [7,] 1.3002208 0.9582693 4.561577 >> >> [8,] 1.6950923 3.5677921 6.005078 >> >> [9,] 0.6509285 0.9025964 5.082288 >> >> [10,] -0.5676040 1.3281102 4.446451 >> >> >> >> #weird moving average of period 1 ! >> >> mma <- apply(m, 2, SMA, n=1) >> >> >> >>> mma >> >> [,1] [,2] [,3] >> >> [1,] NA NA NA >> >> [2,] -1.2174937 0.7356427 4.393279 >> >> [3,] 0.8504074 2.5286509 2.689196 >> >> [4,] 1.8048642 1.8580804 6.665237 >> >> [5,] -0.6749397 1.0944277 4.838608 >> >> [6,] 0.8252034 1.5595268 3.681695 >> >> [7,] 1.3002208 0.9582693 4.561577 >> >> [8,] 1.6950923 3.5677921 6.005078 >> >> [9,] 0.6509285 0.9025964 5.082288 >> >> [10,] -0.5676040 1.3281102 4.446451 >> >> >> >> >> >> #difference should be 0 but here is the result >> >>> m - mma >> >> [,1] [,2] [,3] >> >> [1,] NA NA NA >> >> [2,] 0.000000e+00 0.000000e+00 -8.881784e-16 >> >> [3,] 0.000000e+00 0.000000e+00 -8.881784e-16 >> >> [4,] 0.000000e+00 4.440892e-16 -8.881784e-16 >> >> [5,] -1.110223e-16 4.440892e-16 -8.881784e-16 >> >> [6,] -1.110223e-16 2.220446e-16 -4.440892e-16 >> >> [7,] -2.220446e-16 2.220446e-16 0.000000e+00 >> >> [8,] -2.220446e-16 0.000000e+00 0.000000e+00 >> >> [9,] -3.330669e-16 2.220446e-16 -8.881784e-16 >> >> [10,] -3.330669e-16 4.440892e-16 -8.881784e-16 >> >> >> >> SMA function use runMean >> >> # TTR / R / MovingAverages.R >> >> "SMA" <- function(x, n=10, ...) { # Simple Moving Average >> >> ma <- runMean( x, n ) >> >> if(!is.null(dim(ma))) { >> >> colnames(ma) <- "SMA" >> >> } >> >> return(ma) >> >> } >> >> >> >> >> >> Can anyone explain me that round error type? >> >> Is it possible to reproduce this same error generation in another >> language like C++ or C# ? >> >> >> >> Thanks in advance for your answers >> >> >> >> Regards >> >> >> >> Chris______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. This email and any attachments were sent from a Monsanto email account and may contain confidential and/or privileged information. If you are not the intended recipient, please contact the sender and delete this email and any attachments immediately. Any unauthorized use, including disclosing, printing, storing, copying or distributing this email, is prohibited. All emails and attachments sent to or from Monsanto email accounts may be subject to monitoring, reading, and archiving by Monsanto, including its affiliates and subsidiaries, as permitted by applicable law. Thank you. ______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.