Using results from the R console and R code to generate the name of an object into R script

Question

I'm interested in Using results from the R console and R code to generate the name of an object into R script.

I created a linear regression with 1 IV, where the DV is mpg and the 2 IVs of interest are cyl and disp . I call the generic model code object lm_DVmpg . I used the code paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "") to generate a unique name for the object containing the lm() in the console. I then pasted the result into the script and used that text as the name of the IV specific regression object.

For example, the name of the object using the IV of cyl is lm_DVmpg_IVcyl , and the name of the object disp is lm_DVmpg_IVdisp .

Here is some example code from the console:

> ## first lm
> # ---- NOTE: Iv is  cyl
> # ---- NOTE: creates lm() object
> lm_DVmpg <- lm(mpg~cyl, data = mtcars)
> # ---- NOTE: creates unique name for lm() object
> paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "")
[1] "lm_DVmpg_IVcyl"
> # ---- NOTE: moves lm_DVmpg to object unique to IV used
> lm_DVmpg_IVcyl <- lm_DVmpg

Is there any way to use R code in the R script file to change the name of the lm_DVmpg code in the line lm_DVmpg <- lm(mpg~cyl, data = mtcars) say to lm_DVmpg_IVcyl , derived from the paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "") command, using R code without having to copy/paste the text lm_DVmpg_IVcyl from the console to the appropriate R script line?

Alternatively, is there a way to get the text lm_DVmpg_IVcyl into the line lm_DVmpg_IVcyl <- lm_DVmpg , derived from the paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "") command, using R code without having to copy/paste from the console after running the code paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "") ?

Any help would be appreciated.

FYI, I use a 2013 Macbook Pro with a 2.4 GHz dual-core intel chip, 8 GB of ram, macOS big sur 11.2.2, RStudio Version 1.4.1106, and the R Base Package 4.04.

Thanks.

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The R script I used is below:

# Naming objects from returns on console
# ---- NOTE: will do several linear regressions using the mtcars dataset, with IV and the DV being "mpg"
# ---- NOTE: IVs - cyl, disp

## gives info on dataset
head(mtcars)
str(mtcars)
colnames(mtcars)

## first lm
# ---- NOTE: Iv is  cyl
# ---- NOTE: creates lm() object
lm_DVmpg <- lm(mpg~cyl, data = mtcars)
# ---- NOTE: creates unique name for lm() object
paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "")
# ---- NOTE: moves lm_DVmpg to object unique to IV used
lm_DVmpg_IVcyl <- lm_DVmpg

## second lm
# ---- NOTE: Iv is  disp
# ---- NOTE: creates lm() object
lm_DVmpg <- lm(mpg~disp, data = mtcars)
# ---- NOTE: creates unique name for lm() object
paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "")
# ---- NOTE: moves lm_DVmpg to object unique to IV used
lm_DVmpg_IVdisp <- lm_DVmpg

## displays summaries of regression objects
# ---- NOTE: latest regression object summary
summary(lm_DVmpg)
# ---- NOTE: unique regression objects
lm_DVmpg_IVmpg
lm_DVmpg_IVdisp
# ---- NOTE: lm_DVmpg = lm_DVmpg_IVdisp, since the lm_DVmpg_IVmpg object when IV == disp was the latest lm() to be run

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Here are my results from the console when running the R script.

> # Naming objects from returns on console
> # ---- NOTE: will do several linear regressions using the mtcars dataset, with IV and the DV being "mpg"
> # ---- NOTE: IVs - cyl, disp
> # Naming objects from returns on console
> # ---- NOTE: will do several linear regressions using the mtcars dataset, with IV and the DV being "mpg"
> # ---- NOTE: IVs - cyl, disp
> 
> ## gives info on dataset
> head(mtcars)
                   mpg cyl disp  hp drat    wt  qsec vs am gear carb
Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1
> str(mtcars)
'data.frame':   32 obs. of  11 variables:
 $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...
> colnames(mtcars)
 [1] "mpg"  "cyl"  "disp" "hp"   "drat" "wt"   "qsec" "vs"   "am"   "gear" "carb"
> 
> ## first lm
> # ---- NOTE: Iv is  cyl
> # ---- NOTE: creates lm() object
> lm_DVmpg <- lm(mpg~cyl, data = mtcars)
> # ---- NOTE: creates unique name for lm() object
> paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "")
[1] "lm_DVmpg_IVcyl"
> # ---- NOTE: moves lm_DVmpg to object unique to IV used
> lm_DVmpg_IVcyl <- lm_DVmpg
> 
> ## second lm
> # ---- NOTE: Iv is  disp
> # ---- NOTE: creates lm() object
> lm_DVmpg <- lm(mpg~disp, data = mtcars)
> # ---- NOTE: creates unique name for lm() object
> paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "")
[1] "lm_DVmpg_IVdisp"
> # ---- NOTE: moves lm_DVmpg to object unique to IV used
> lm_DVmpg_IVdisp <- lm_DVmpg
> 
> ## displays summaries of regression objects
> # ---- NOTE: latest regression object summary
> summary(lm_DVmpg)

Call:
lm(formula = mpg ~ disp, data = mtcars)

Residuals:
    Min      1Q  Median      3Q     Max 
-4.8922 -2.2022 -0.9631  1.6272  7.2305 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 29.599855   1.229720  24.070  < 2e-16 ***
disp        -0.041215   0.004712  -8.747 9.38e-10 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 3.251 on 30 degrees of freedom
Multiple R-squared:  0.7183,    Adjusted R-squared:  0.709 
F-statistic: 76.51 on 1 and 30 DF,  p-value: 9.38e-10

> # ---- NOTE: unique regression objects
> lm_DVmpg_IVmpg

Call:
lm(formula = mpg ~ cyl, data = mtcars)

Coefficients:
(Intercept)          cyl  
     37.885       -2.876  

> lm_DVmpg_IVdisp

Call:
lm(formula = mpg ~ disp, data = mtcars)

Coefficients:
(Intercept)         disp  
   29.59985     -0.04122  

> # ---- NOTE: lm_DVmpg = lm_DVmpg_IVdisp, since the lm_DVmpg_IVmpg object when IV == disp was the latest lm() to be run

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Answer 1

I am not sure why you need this but I think assign + get is what you are looking for.

lm_DVmpg <- lm(mpg~cyl, data = mtcars)
new_name <- paste("lm_DVmpg","_IV", as.character(lm_DVmpg$call$formula[[3]]), sep = "")
assign(new_name, lm(mpg~disp, data = mtcars))  
get(new_name)

#Call:
#lm(formula = mpg ~ disp, data = mtcars)

#Coefficients:
#(Intercept)         disp  
#   29.59985     -0.04122