Apply same linear model to subset of dataframe

There is a slight problem with the code. Due to the collapse=?+? argument,
the code only works if there are >1 predictor variables. How can I amend
code so it also works if number of predictor variable==1?

# WORKING ? LENGTH OF EACH SET OF PREDICTOR >1

DV <- c("mpg", "drat", "gear")
IV <- list(c("cyl", "disp", "hp"), c("wt", "qsec"), c("carb", "hp"))
fits <- vector("list", length(DV))

for(i in seq(DV)) {
 fit <- lm(formula=paste(DV[i], paste(IV[[i]], collapse="+"), sep="~"),
data=mtcars) 
 plot(fit$fitted, fit$resid, main=paste("DV", DV[i], sep="="))
 lapply(fit$model[, -1], function(x) plot(x, fit$resid))
 fits[[i]] <- fit 
}

# NOT WORKING ? LENGTH OF LAST PREDICTOR (CARB) ==1

DV <- c("mpg", "drat", "gear")
IV <- list(c("cyl", "disp", "hp"), c("wt", "qsec"), c("carb"))
fits <- vector("list", length(DV))

for(i in seq(DV)) {
 fit <- lm(formula=paste(DV[i], paste(IV[[i]], collapse="+"), sep="~"),
data=mtcars) 
 plot(fit$fitted, fit$resid, main=paste("DV", DV[i], sep="="))
 lapply(fit$model[, -1], function(x) plot(x, fit$resid))

 fits[[i]] <- fit 
}

Many thanks
Ross

From:  Jean V Adams <jvadams at usgs.gov>
Date:  Tuesday, 6 November 2012 19:20
To:  Ross Ahmed <rossahmed at googlemail.com>
Cc:  <r-help at r-project.org>
Subject:  Re: [R] Apply same linear model to subset of dataframe

Ross,

You can store the lm() results in a list, if you like.
For example:

DV <- c("mpg", "drat", "gear")
IV <- list(c("cyl", "disp", "hp"), c("wt", "qsec"), c("carb", "hp"))
fits <- vector("list", length(DV))

for(i in seq(DV)) {
       fit <- lm(formula=paste(DV[i], paste(IV[[i]], collapse="+"),
sep="~"), data=mtcars)
       plot(fit$fitted, fit$resid, main=paste("DV", DV[i], sep="="))
       lapply(fit$model[, -1], function(x) plot(x, fit$resid))
       fits[[i]] <- fit
       }

Jean



Ross Ahmed <rossahmed at googlemail.com> wrote on 11/06/2012 09:25:13 AM:

Thanks Jean

This works for the plots, but it only stores the last lm() computed

Ross

From: Jean V Adams <jvadams at usgs.gov>
Date: Tuesday, 6 November 2012 14:12
To: Ross Ahmed <rossahmed at googlemail.com>
Cc: <r-help at r-project.org>
Subject: Re: [R] Apply same linear model to subset of dataframe

Ross,

Here's one way to condense the code ...

DV <- c("mpg", "drat", "gear")
IV <- list(c("cyl", "disp", "hp"), c("wt", "qsec"), c("carb", "hp"))

for(i in seq(DV)) {
       fit <- lm(formula=paste(DV[i], paste(IV[[i]], collapse="+"),
sep="~"), data=mtcars)
       plot(fit$fitted, fit$resid, main=paste("DV", DV[i], sep="="))
       lapply(fit$model[, -1], function(x) plot(x, fit$resid))
       }

Jean



Ross Ahmed <rossahmed at googlemail.com> wrote on 11/04/2012 09:57:34 AM:

I have applied the same linear model to several different subsets of a
dataset. I recently read that in R, code should never be repeated.I feel my
code as it currently stands has a lot of repetition, which could be
condensed into fewer lines. I will use the mtcars dataset to replicatewhat
I have done. My question is: how can I use fewer lines of code (for example
using a for loop, a function or plyr) to achieve the same output as below?

data(mtcars)

# Apply the same model to the dataset but choosing different combinations of
dependent (DV) and independent (IV) variables in each case:
lm.mpg= lm(mpg~cyl+disp+hp, data=mtcars)
lm.drat = lm(drat~wt+qsec, data=mtcars)
lm.gear = lm(gear~carb+hp, data=mtcars)

# Plot residuals against fitted values for each model
plot(lm.mpg$fitted,lm.mpg$residuals, main = "lm.mpg")
plot(lm.drat$fitted,lm.drat$residuals, main = "lm.drat")
plot(lm.gear$fitted,lm.gear$residuals, main = "lm.gear")

# Plot residuals against IVs for each model
plotResIV <- function (IV,lmResiduals)
 {
 lapply(IV, function (x) plot(x,lmResiduals))
}

plotResIV(lm.mpg$model[,-1],lm.mpg$residuals)
plotResIV(lm.drat$model[,-1],lm.drat$residuals)
plotResIV(lm.gear$model[,-1],lm.gear$residuals)

Many thanks
Ross Ahmed

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