I have a data frame and I did a linear model. I want to extract the coefficients and store each coefficient into a variable using R. This is my data frame
df <- mtcars
fit <- lm(mpg~., data = df)
This is how I extract one coefficient
beta_0 = fit$coefficients[1]
I want to do this automatically for all coefficients in my model. I tried to use a loop but is not working. I know is not the right code but that was what I found
for (i in fit$coefficients(1:11)) {
d["s{0}".format(x)] = variable1
}
df <- mtcars
fit <- lm(mpg~., data = df)
beta_0 = fit$coefficients[1]
#base R approach
coef_base <- coef(fit)
coef_base
#> (Intercept) cyl disp hp drat wt
#> 12.30337416 -0.11144048 0.01333524 -0.02148212 0.78711097 -3.71530393
#> qsec vs am gear carb
#> 0.82104075 0.31776281 2.52022689 0.65541302 -0.19941925
#tidyverse approach with the broom package
coef_tidy <- broom::tidy(fit)
coef_tidy
#> # A tibble: 11 x 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept) 12.3 18.7 0.657 0.518
#> 2 cyl -0.111 1.05 -0.107 0.916
#> 3 disp 0.0133 0.0179 0.747 0.463
#> 4 hp -0.0215 0.0218 -0.987 0.335
#> 5 drat 0.787 1.64 0.481 0.635
#> 6 wt -3.72 1.89 -1.96 0.0633
#> 7 qsec 0.821 0.731 1.12 0.274
#> 8 vs 0.318 2.10 0.151 0.881
#> 9 am 2.52 2.06 1.23 0.234
#> 10 gear 0.655 1.49 0.439 0.665
#> 11 carb -0.199 0.829 -0.241 0.812
for (i in coef_base) {
#do work on i
print(i)
}
#> [1] 12.30337
#> [1] -0.1114405
#> [1] 0.01333524
#> [1] -0.02148212
#> [1] 0.787111
#> [1] -3.715304
#> [1] 0.8210407
#> [1] 0.3177628
#> [1] 2.520227
#> [1] 0.655413
#> [1] -0.1994193