Predictive Hacks

How to Store Models in R with a for loop

Let’s say that we want to run a different regression model for each Species in iris dataset. We can do it in two different ways as follows:

Store the models in a list

my_models<-list()

for (s in unique(iris$Species)) {
    tmp<-iris[iris$Species==s,]
    my_models[[s]]<-lm(Sepal.Length~Sepal.Width+Petal.Length+Petal.Width, data=tmp)
}

# get the 'setosa' model
my_models[['setosa']]
Call:
lm(formula = Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width, 
    data = tmp)

Coefficients:
 (Intercept)   Sepal.Width  Petal.Length   Petal.Width  
      2.3519        0.6548        0.2376        0.2521  

Store the models by name using the assign

for (s in unique(iris$Species)) {
    tmp<-iris[iris$Species==s,]
    assign(s,lm(Sepal.Length~Sepal.Width+Petal.Length+Petal.Width, data=tmp))
}

# get the 'setosa' model
get("setosa")
Call:
lm(formula = Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width, 
    data = tmp)

Coefficients:
 (Intercept)   Sepal.Width  Petal.Length   Petal.Width  
      2.3519        0.6548        0.2376        0.2521  

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