I have a foreach loop that runs regressions in parallel and works fine, but when I try to add the weights parameter to the regression the coefficients don?t get stored in the ?models? variable like they are supposed to. Below is my reproducible example: library(doParallel) cl <- makeCluster(4) registerDoParallel(cl) fmla <- as.formula("y ~ .") models <- foreach(d=1:10, .combine=rbind, .errorhandling='remove') %dopar% { datdf <- data.frame(y = 1:100+2*rnorm(100), x = 1:100+rnorm(100)) weights <- rep(c(1,2), 50) mod <- lm(fmla, data=datdf, weights=weights) #mod <- lm(fmla, data=datdf) return(mod$coef) } models You can change the commenting on the two ?mod <-? lines to see that the non-weighted one works and the weighted regression doesn?t work. I tried using .export="weights" in the foreach line, but R says that weights is already being exported. Thanks in advance for any suggestions. *************************************************************** This message and any attachments are for the intended recipient's use only. This message may contain confidential, proprietary or legally privileged information. No right to confidential or privileged treatment of this message is waived or lost by an error in transmission. If you have received this message in error, please immediately notify the sender by e-mail, delete the message, any attachments and all copies from your system and destroy any hard copies. You must not, directly or indirectly, use, disclose, distribute, print or copy any part of this message or any attachments if you are not the intended recipient.
Dear Roger, Maybe you want to return(mod) instead of return(mod$coef) Best regards, ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance Kliniekstraat 25 1070 Anderlecht Belgium To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey 2016-10-07 15:24 GMT+02:00 Bos, Roger <roger.bos at rothschild.com>:> I have a foreach loop that runs regressions in parallel and works fine, > but when I try to add the weights parameter to the regression the > coefficients don?t get stored in the ?models? variable like they are > supposed to. Below is my reproducible example: > > library(doParallel) > cl <- makeCluster(4) > registerDoParallel(cl) > fmla <- as.formula("y ~ .") > models <- foreach(d=1:10, .combine=rbind, .errorhandling='remove') %dopar% > { > datdf <- data.frame(y = 1:100+2*rnorm(100), x = 1:100+rnorm(100)) > weights <- rep(c(1,2), 50) > mod <- lm(fmla, data=datdf, weights=weights) > #mod <- lm(fmla, data=datdf) > return(mod$coef) > } > models > > You can change the commenting on the two ?mod <-? lines to see that the > non-weighted one works and the weighted regression doesn?t work. I tried > using .export="weights" in the foreach line, but R says that weights is > already being exported. > > Thanks in advance for any suggestions. > > > > > > *************************************************************** > This message and any attachments are for the intended recipient's use only. > This message may contain confidential, proprietary or legally privileged > information. No right to confidential or privileged treatment > of this message is waived or lost by an error in transmission. > If you have received this message in error, please immediately > notify the sender by e-mail, delete the message, any attachments and all > copies from your system and destroy any hard copies. You must > not, directly or indirectly, use, disclose, distribute, > print or copy any part of this message or any attachments if you are not > the intended recipient. > > ______________________________________________ > 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.[[alternative HTML version deleted]]
All, I figured out how to get it to work, so I am posting the solution in case anyone is interested. I had to use attr to set the weights as an attribute of the data object for the linear model. Seems convoluted, but anytime I tried to pass a named vector as the weights the foreach loop could not find the variable, even if I tried exporting it. If anybody knows of a better way please let me know as this does not seem ideal to me, but it works. library(doParallel) cl <- makeCluster(4) registerDoParallel(cl) fmla <- as.formula("y ~ .") models <- foreach(d=1:10, .combine=rbind, .errorhandling='pass') %dopar% { datdf <- data.frame(y = 1:100+2*rnorm(100), x = 1:100+rnorm(100)) attr(datdf, "weights") <- rep(c(1,2), 50) mod <- lm(fmla, data=datdf, weights=attr(data, "weights")) return(mod$coef) } Models -----Original Message----- From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Bos, Roger Sent: Friday, October 07, 2016 9:25 AM To: R-help Subject: [R] weighted regression inside FOREACH loop I have a foreach loop that runs regressions in parallel and works fine, but when I try to add the weights parameter to the regression the coefficients don?t get stored in the ?models? variable like they are supposed to. Below is my reproducible example: library(doParallel) cl <- makeCluster(4) registerDoParallel(cl) fmla <- as.formula("y ~ .") models <- foreach(d=1:10, .combine=rbind, .errorhandling='remove') %dopar% { datdf <- data.frame(y = 1:100+2*rnorm(100), x = 1:100+rnorm(100)) weights <- rep(c(1,2), 50) mod <- lm(fmla, data=datdf, weights=weights) #mod <- lm(fmla, data=datdf) return(mod$coef) } models You can change the commenting on the two ?mod <-? lines to see that the non-weighted one works and the weighted regression doesn?t work. I tried using .export="weights" in the foreach line, but R says that weights is already being exported. Thanks in advance for any suggestions. *************************************************************** This message and any attachments are for the intended recipient's use only. This message may contain confidential, proprietary or legally privileged information. No right to confidential or privileged treatment of this message is waived or lost by an error in transmission. If you have received this message in error, please immediately notify the sender by e-mail, delete the message, any attachments and all copies from your system and destroy any hard copies. You must not, directly or indirectly, use, disclose, distribute, print or copy any part of this message or any attachments if you are not the intended recipient. ______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
A more general way is to change the environment of your formula to a child of its original environment and add variables like 'weights' or 'subset' to the child environment. Since you change the environment inside a function call it won't affect the formula outside of the function call. E.g. fmla <- as.formula("y ~ .") models <- foreach(d=1:10, .combine=rbind, .errorhandling='remove') %dopar% { datdf <- data.frame(y = 1:100+2*rnorm(100), x = 1:100+rnorm(100)) localEnvir <- new.env(parent=environment(fmla)) environment(fmla) <- localEnvir localEnvir$weights <- rep(c(1,2), 50) mod <- lm(fmla, data=datdf, weights=weights) return(mod$coef) } models # (Intercept) x #result.1 -0.16910860 1.0022022 #result.2 0.03326814 0.9968325 #result.3 -0.08177174 1.0022907 #... environment(fmla) #<environment: R_GlobalEnv> Bill Dunlap TIBCO Software wdunlap tibco.com On Fri, Oct 7, 2016 at 7:44 AM, Bos, Roger <roger.bos at rothschild.com> wrote:> All, > > I figured out how to get it to work, so I am posting the solution in case > anyone is interested. I had to use attr to set the weights as an attribute > of the data object for the linear model. Seems convoluted, but anytime I > tried to pass a named vector as the weights the foreach loop could not find > the variable, even if I tried exporting it. If anybody knows of a better > way please let me know as this does not seem ideal to me, but it works. > > library(doParallel) > cl <- makeCluster(4) > registerDoParallel(cl) > fmla <- as.formula("y ~ .") > models <- foreach(d=1:10, .combine=rbind, .errorhandling='pass') %dopar% { > datdf <- data.frame(y = 1:100+2*rnorm(100), x = 1:100+rnorm(100)) > attr(datdf, "weights") <- rep(c(1,2), 50) > mod <- lm(fmla, data=datdf, weights=attr(data, "weights")) > return(mod$coef) > } > Models > > > > > > -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Bos, Roger > Sent: Friday, October 07, 2016 9:25 AM > To: R-help > Subject: [R] weighted regression inside FOREACH loop > > I have a foreach loop that runs regressions in parallel and works fine, > but when I try to add the weights parameter to the regression the > coefficients don?t get stored in the ?models? variable like they are > supposed to. Below is my reproducible example: > > library(doParallel) > cl <- makeCluster(4) > registerDoParallel(cl) > fmla <- as.formula("y ~ .") > models <- foreach(d=1:10, .combine=rbind, .errorhandling='remove') %dopar% > { > datdf <- data.frame(y = 1:100+2*rnorm(100), x = 1:100+rnorm(100)) > weights <- rep(c(1,2), 50) > mod <- lm(fmla, data=datdf, weights=weights) > #mod <- lm(fmla, data=datdf) > return(mod$coef) > } > models > > You can change the commenting on the two ?mod <-? lines to see that the > non-weighted one works and the weighted regression doesn?t work. I tried > using .export="weights" in the foreach line, but R says that weights is > already being exported. > > Thanks in advance for any suggestions. > > > > > > *************************************************************** > This message and any attachments are for the intended recipient's use only. > This message may contain confidential, proprietary or legally privileged > information. No right to confidential or privileged treatment of this > message is waived or lost by an error in transmission. > If you have received this message in error, please immediately notify the > sender by e-mail, delete the message, any attachments and all copies from > your system and destroy any hard copies. You must not, directly or > indirectly, use, disclose, distribute, print or copy any part of this > message or any attachments if you are not the intended recipient. > > ______________________________________________ > 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. > ______________________________________________ > 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.[[alternative HTML version deleted]]