Try variations of this: library(leaps) b<-regsubsets(Fertility~.,data=swiss) w <- summary(b)$which lapply(1:nrow(w), function(i) coef(lm(Fertility ~., swiss[w[i, ]])))
On Fri, Dec 26, 2008 at 1:57 PM, Murtaza Das <murtaza...@gmail.com> wrote: > Thanks for replying Gabor. > > I checked the leaps() function and i think it is intended to find the > best combination of predictors in the linear model. > Does leaps have a way to combine different factor columns in my data > frame as follows : > > I have the regression model fixed. The combination of predictor > variables used always remains the same. > UncDmd ~ M1 + M2 + M3 + M4 + M5 + M6 + M7 + M8 + M9 + M10 + M11 > > I want to get the coefficients in this linear model when different > combinations of factors (select a combination from first four columns > of the data frame) and their levels are taken from a data frame(apply > lm model for a each combination of levels within the selected factor > columns). Thus corresponding to each combination, the data used to > determine the model coefficients will be different. > > I am attaching the data and R files (long method using loops) that I > use to get the result. Currently, I modify keys to get different > combinations. Also, note in the script, the data frame is named LRO1. > > Thanks again, > Murtaza > > > On Fri, Dec 26, 2008 at 12:58 PM, Gabor Grothendieck > <ggrothendi...@gmail.com> wrote: >> See the leaps package. >> >> On Fri, Dec 26, 2008 at 12:37 PM, Murtaza Das <murtaza...@gmail.com> wrote: >>> Hi, >>> >>> I am trying to find an efficient way of applying a linear regression >>> model to different factor combinations in a data frame. >>> I want to obtain the output with minimal or no use of loops if >>> possible. Please let me know if this query is unclear. >>> >>> Thanks, >>> Murtaza >>> >>> *********************************************************************************************************************************************************** >>> >>> The data frame TEST1 has four factor columns followed by thirteen >>> numeric columns defined as : >>> 1) Community, levels: "20232" >>> 2) WT, levels: "B", "E", "M" >>> 3) LTC, levels: "L", "M", "S", "1" >>> 4) UC, levels: "1X1", "2X2" >>> 5) UncDmd: Response variable in the linear model >>> 6-16) M1...M11: Explanatory variables in the linear model >>> >>> A few sample rows in the data frame are as follows: >>>> TEST1[1:15,] >>> Community WT LTC UC UncDmd M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 >>> 1 20232 E L 1X1 1.000000 0 0 0 0 0 0 0 0 0 0 1 >>> 2 20232 E L 2X2 0.000000 0 0 0 0 0 0 0 0 0 0 1 >>> 3 20232 E M 1X1 1.000000 0 0 0 0 0 0 0 0 0 0 1 >>> 4 20232 E M 2X2 1.000000 0 0 0 0 0 0 0 0 0 0 1 >>> 5 20232 E S 1X1 0.000000 0 0 0 0 0 0 0 0 0 0 1 >>> 6 20232 E S 2X2 0.000000 0 0 0 0 1 0 0 0 0 0 0 >>> 7 20232 B 1 1X1 0.209117 0 0 0 0 0 0 0 0 0 0 1 >>> 8 20232 B 1 2X2 0.190605 0 0 0 0 0 0 0 0 0 0 1 >>> 9 20232 B L 1X1 0.000000 0 0 0 0 1 0 0 0 0 0 0 >>> 10 20232 B L 2X2 1.000000 0 0 0 0 0 0 0 0 0 0 1 >>> 11 20232 B M 1X1 4.000000 0 0 0 0 0 0 0 0 0 0 1 >>> 12 20232 B M 2X2 0.000000 0 0 0 0 0 0 0 0 0 0 1 >>> 13 20232 B S 1X1 0.000000 1 0 0 0 0 0 0 0 0 0 0 >>> 14 20232 B S 2X2 0.000000 0 0 0 0 0 0 0 0 0 0 1 >>> 15 20232 M 1 1X1 0.618689 0 0 0 0 0 0 0 0 0 1 0 >>> >>> ********************************************************************************************************************************************************* >>> I need to store the coefficients using lm() for different combinations >>> of the 4 factors, or different combinations of 3 factors or different >>> combinations of 2 factors or >>> differennt combinations of 1 factor. >>> The formula remains fixed as: >>>> Formula >>> UncDmd ~ M1 + M2 + M3 + M4 + M5 + M6 + M7 + M8 + M9 + M10 + M11 >>> >>> So, different models I want to solve in R are : >>> 1) Community : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") ) , ]) >>> 2) WT : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="B") ) , ]) >>> 3) WT : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="E") ) , ]) >>> 4) WT : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="M") ) , ]) >>> 5) LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[3]]=="L") ) , ]) >>> 6) LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[3]]=="M") ) , ]) >>> 7) LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[3]]=="S") ) , ]) >>> 8) LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[3]]=="1L") ) , ]) >>> 9) UC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[4]]=="1X1") ) , ]) >>> 10) UC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[4]]=="2X2") ) , ]) >>> 11) Community, WT : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[2]]=="B") ) , ]) >>> 12) Community, WT : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[2]]=="E") ) , ]) >>> 13) Community, WT : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[2]]=="M") ) , ]) >>> 14) Community, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[3]]=="L") ) , ]) >>> 15) Community, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[3]]=="M") ) , ]) >>> 16) Community, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[3]]=="S") ) , ]) >>> 17) Community, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[3]]=="1") ) , ]) >>> 18) Community, UC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[4]]=="1X1") ) , ]) >>> 19) Community, UC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[4]]=="2X2") ) , ]) >>> 20) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="B") * (TEST1[[3]]=="L") ) , ]) >>> 21) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="B") * (TEST1[[3]]=="M") ) , ]) >>> 22) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="B") * (TEST1[[3]]=="S") ) , ]) >>> 23) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="B") * (TEST1[[3]]=="1") ) , ]) >>> 24) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="E") * (TEST1[[3]]=="L") ) , ]) >>> 25) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="E") * (TEST1[[3]]=="M") ) , ]) >>> 26) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="E") * (TEST1[[3]]=="S") ) , ]) >>> 27) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="E") * (TEST1[[3]]=="1") ) , ]) >>> 28) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="M") * (TEST1[[3]]=="L") ) , ]) >>> 29) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="M") * (TEST1[[3]]=="M") ) , ]) >>> 30) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="M") * (TEST1[[3]]=="S") ) , ]) >>> 31) WT, LTC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[2]]=="M") * (TEST1[[3]]=="1") ) , ]) >>> 32) WT, UC : >>> ... >>> ... >>> xx) LTC, UC : >>> ... >>> xxx) Community, WT, LTC : >>> ... >>> ... >>> and so on upto: >>> xxxx) Community, WT, LTC, UC : lm(Formula,TEST1[ as.logical( >>> (TEST1[[1]]=="20232") * (TEST1[[2]]=="M") * (TEST1[[3]]=="1") ) * >>> (TEST1[[4]]=="2X2"), ]) >>> *********************************************************************************************************************************************************** >>> Desired Output format (or something simlar): >>> Factor1 Factor2 Factor3 Factor4 Intercept M1 M2 M3 M4 M5 M6 >>> M7 M8 M9 M10 M11 >>> 1) 20232 x x x >>> x x x x x x x x x >>> 2) B x x x >>> x x x x x x x x x >>> 3) E x x x >>> x x x x x x x x x >>> 4) M x x x >>> x x x x x x x x x >>> 5) L x x x >>> x x x x x x x x x >>> 6) M x x x >>> x x x x x x x x x >>> 7) S x x x >>> x x x x x x x x x >>> 8) 1 x x x >>> x x x x x x x x x >>> 9) 1X1 x x x >>> x x x x x x x x x >>> 10) 2X2 x x x >>> x x x x x x x x x >>> 11) 20232 B x x x x >>> x x x x x x x x >>> .. >>> .. >>> and so on.. >>> >>> >>> x is the respective coefficient obtained from the linear fit. >>> >>> ______________________________________________ >>> R-help@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. >>> >> > ______________________________________________ R-help@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.
