Subject: Regress multiple independent variables on multiple dependent variables
Hi, This gives an error.? glm(cbind(O3, temp) ~ ., data=ozone) Error in x[good, , drop = FALSE] : (subscript) logical subscript too long ?lm(cbind(O3, temp) ~ ., data=ozone) #works R version 3.0.2 (2013-09-25) Platform: x86_64-unknown-linux-gnu (64-bit) locale: ?[1] LC_CTYPE=en_CA.UTF-8?????? LC_NUMERIC=C????????????? ?[3] LC_TIME=en_CA.UTF-8??????? LC_COLLATE=en_CA.UTF-8??? ?[5] LC_MONETARY=en_CA.UTF-8??? LC_MESSAGES=en_CA.UTF-8?? ?[7] LC_PAPER=en_CA.UTF-8?????? LC_NAME=C???????????????? ?[9] LC_ADDRESS=C?????????????? LC_TELEPHONE=C??????????? [11] LC_MEASUREMENT=en_CA.UTF-8 LC_IDENTIFICATION=C?????? attached base packages: [1] stats???? graphics? grDevices utils???? datasets? methods?? base???? other attached packages: [1] faraway_1.0.5?? ggplot2_0.9.3.1 plotrix_3.5-1?? stringr_0.6.2? [5] reshape2_1.2.2 loaded via a namespace (and not attached): ?[1] colorspace_1.2-3?? dichromat_2.0-0??? digest_0.6.3?????? grid_3.0.2??????? ?[5] gtable_0.1.2?????? labeling_0.2?????? MASS_7.3-29??????? munsell_0.4.2???? ?[9] plyr_1.8?????????? proto_0.3-10?????? RColorBrewer_1.0-5 scales_0.2.3????? [13] tcltk_3.0.2??????? tools_3.0.2??????
On Monday, November 4, 2013 8:55 AM, Michael Friendly <friendly at yorku.ca> wrote:
It's not clear exactly what you mean by 'automate' but you can simplify a bit by fitting a multivariate linear model to all the responses together, and using . on the RHS of the formula to represent all other variables in the data set as independent variables, m.all <- glm(cbind(O3, temp) ~ ., data=ozone) (assuming that only humidity, ibh and ibt remain; otherwise, use data=subset(ozone, ...)) -Michael
On 11/4/2013 2:55 AM, Kumar Raj wrote:
I want to estimate the effect of several independent variables on several dependent variables. In the example below I wanted to estimate the effect of three independent variables on ozone and temperature.? My aim is to create a list of dependent and independent variables and automate the process rather than writing every dependent and independent variable in each model as I have done below. Example data is provided by the following library: library(faraway) data(ozone) mo3 <- glm(O3 ~ humidity + ibh + ibt, data=ozone) mtemp<- glm(temp ~? humidity + ibh + ibt, data=ozone) Thanks ??? [[alternative HTML version deleted]]
Michael Friendly? ? Email: friendly AT yorku DOT ca Professor, Psychology Dept. & Chair, Quantitative Methods York University? ? ? Voice: 416 736-2100 x66249 Fax: 416 736-5814 4700 Keele Street? ? Web:? http://www.datavis.ca Toronto, ONT? M3J 1P3 CANADA ______________________________________________ R-help at r-project.org mailing list 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.