Creating data frame with residuals of a data frame
try this:
age<- c(5,6,10,14,16,NA,18)
value1<- c(30,70,40,50,NA,NA,NA)
value2<- c(2,4,1,4,4,4,4)
df<- data.frame(age, value1, value2)
#Run linear regression to adjust for age and get residuals:
lm_f <- function(x) {
+ x<- residuals(lm(data=df, formula= x ~ age)) + }
resid <- apply(df,2,lm_f)
resid<- resid[-1]
for (i in names(resid)){
+ newCol <- paste(i, 'res', sep = '') + df[[newCol]] <- NA # initialize + df[[newCol]][as.integer(names(resid[[i]]))] <- resid[[i]] + }
df
age value1 value2 value1res value2res 1 5 30 2 -16.945813 -0.37398374 2 6 70 4 22.906404 1.50406504 3 10 40 1 -7.684729 -1.98373984 4 14 50 4 1.724138 0.52845528 5 16 NA 4 NA 0.28455285 6 NA NA 4 NA NA 7 18 NA 4 NA 0.04065041 On Mon, Oct 24, 2011 at 10:23 AM, francesca casalino
<francy.casalino at gmail.com> wrote:
Dear experts,
I am trying to create a data frame from the residuals I get after
having applied a linear regression to each column of a data frame, but
I don't know how to create this data frame from the resulting list
since the list has differing numbers of rows.
So for example:
age<- c(5,6,10,14,16,NA,18)
value1<- c(30,70,40,50,NA,NA,NA)
value2<- c(2,4,1,4,4,4,4)
df<- data.frame(age, value1, value2)
#Run linear regression to adjust for age and get residuals:
lm_f <- function(x) {
x<- residuals(lm(data=df, formula= x ~ age))
}
resid <- apply(df,2,lm_f)
resid<- resid[-1]
Then resid is a list with different row numbers:
$value1
? ? ? ? 1 ? ? ? ? ?2 ? ? ? ? ?3 ? ? ? ? ?4
-16.945813 ?22.906404 ?-7.684729 ? 1.724138
$value2
? ? ? ? ?1 ? ? ? ? ? 2 ? ? ? ? ? 3 ? ? ? ? ? 4 ? ? ? ? ? 5 ? ? ? ? ? 7
-0.37398374 ?1.50406504 -1.98373984 ?0.52845528 ?0.28455285 ?0.04065041
I am trying to get both the original variable and their residuals in
the same data frame like this:
age, value1, value2, resid_value1, resid_value2
But when I try cbind or other operations I get an error message
because they do not have the same number of rows. Can you please help
me figure out how to solve this?
Thank you.
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