passing a vector of variables into lm() formula

问题:

I was trying to automate a piece of my code so that programming become less tedious. Basically I was trying to do a stepwise selection of variables using fastbw() in the rms package. I would like to pass the list of variables selected by fastbw() into a formula as y ~ x1+x2+x3, "x1" "x2" "x3" being the list of variables selected by fastbw()

Here is the code I tried and did not work

olsOAW0.r060 <- ols(roll_pct~byoy+trans_YoY+change18m, 
                    subset= helper=="POPNOAW0_r060", 
                    na.action = na.exclude, 
                    data = modelready)

OAW0 <- fastbw(olsOAW0.r060, rule="p", type="residual", sls= 0.05)

vec <- as.vector(OAW0$names.kept, mode="any")

b <- paste(vec, sep ="+") ##I even tried b <- paste(OAW0$names.kept, sep="+")

bestp.OAW0.r060 <- lm(roll_pct ~ b , 
                      data = modelready, 
                      subset = helper =="POPNOAW0_r060",    
                      na.action = na.exclude)

I am new to R and still havent trailed the steep learning curve, so apologize for obvious programming blunders. Any help is much appreciated

回答1:

You're almost there. You just have to paste the entire formula together, something like this:

paste("roll_pct ~ ",b,sep = "")

coerce it to an actual formula using as.formula and then pass that to lm. Technically, I think lm may coerce a character string itself, but coercing it yourself is generally safer. (Some functions that expect formulas won't do the coercion for you, others will.)

回答2:

You would actually need to use collapse instead of seb when defining b.

b <- paste(OAW0$names.kept, collapse="+")

Then you can put it in joran answer

paste("roll_pct ~ ",b,sep = "")

or just use:

paste("roll_pct ~ ",paste(OAW0$names.kept, collapse="+"),sep = "")

回答3:

I ran into similar issue today, if you want to make it even more generic where you don't even have to have fixed class name, you can use

frmla <- as.formula(paste(colnames(modelready)[1], paste(colnames(modelready)[2:ncol(modelready)], sep = "", 
                              collapse = " + "), sep = " ~ "))

This assumes that you have class variable or the dependent variable in the first column but indexing can be easily switched to last column as:

frmla <- as.formula(paste(colnames(modelready)[ncol(modelready)], paste(colnames(modelready)[1:(ncol(modelready)-1)], sep = "", 
                              collapse = " + "), sep = " ~ "))

Then continue with lm using:

bestp.OAW0.r060 <- lm(frmla , data = modelready, ... )

回答4:

If you're looking for something less verbose:

fm <- as.formula( paste( colnames(df)[i], ".", sep=" ~ ")) 
                                      # i is the index of the outcome column

Here it is in a function:

getFormula<-function(target, df) {

  i <- grep(target,colnames(df))
  as.formula(paste(colnames(df)[i], 
                   ".", 
                   sep = " ~ "))
}
fm <- getFormula("myOutcomeColumnName", myDataFrame)
rp <- rpart(fm, data = myDataFrame) # Use the formula to build a model

回答5:

just to simplify and collect above answers, based on a function

my_formula<- function(colPosition, trainSet){
    dep_part<- paste(colnames(trainSet)[colPosition],"~",sep=" ")
    ind_part<- paste(colnames(trainSet)[-colPosition],collapse=" + ")
    dt_formula<- as.formula(paste(dep_part,ind_part,sep=" "))
    return(dt_formula)
}

To use it:

my_formula( dependent_var_position, myTrainSet)