CODEWITHSUNDEEP
rregression
Michael Schubert
Michael Schubert

Reputation: 2796

forward stepwise regression

In R stepwise forward regression, I specify a minimal model and a set of variables to add (or not to add):

min.model = lm(y ~ 1)
fwd.model = step(min.model, direction='forward', scope=(~ x1 + x2 + x3 + ...))

Is there any way to specify using all variables in a matrix/data.frame, so I don't have to enumerate them?

Examples to illustrate what I'd like to do, but they don't work:

# 1
fwd.model = step(min.model, direction='forward', scope=(~ ., data=my.data.frame))

# 2
min.model = lm(y ~ 1, data=my.data.frame)
fwd.model = step(min.model, direction='forward', scope=(~ .))

Upvotes: 19

Views: 62961

Answers (3)

shiny
shiny

Reputation: 3502

You can do it in one step like this

fwd.model = step(lm(y ~ 1, data=my.data.frame), 
                 direction='forward', scope=~ x1 + x2 + x3 + ...)

Upvotes: 3

husky li
husky li

Reputation: 1

The function step resembles the funciton stepAIC in MASS package, following is an example from ?stepAIC

quine.stp <- stepAIC(quine.nxt,
    scope = list(upper = ~Eth*Sex*Age*Lrn, lower = ~1),
    trace = FALSE)

Upvotes: 0

Stephan Kolassa
Stephan Kolassa

Reputation: 8335

scope expects (quoting the help page ?step)

either a single formula, or a list containing components ‘upper’ and ‘lower’, both formulae. See the details for how to specify the formulae and how they are used.

You can extract and use the formula corresponding to "~." like this:

> my.data.frame=data.frame(y=rnorm(20),foo=rnorm(20),bar=rnorm(20),baz=rnorm(20))
> min.model = lm(y ~ 1, data=my.data.frame)
> biggest <- formula(lm(y~.,my.data.frame))
> biggest
y ~ foo + bar + baz
> fwd.model = step(min.model, direction='forward', scope=biggest)
Start:  AIC=0.48
y ~ 1

       Df Sum of Sq    RSS      AIC
+ baz   1    2.5178 16.015 -0.44421
<none>              18.533  0.47614
+ foo   1    1.3187 17.214  0.99993
+ bar   1    0.4573 18.075  1.97644

Step:  AIC=-0.44
y ~ baz

       Df Sum of Sq    RSS      AIC
<none>              16.015 -0.44421
+ foo   1   0.41200 15.603  1.03454
+ bar   1   0.20599 15.809  1.29688
>

Upvotes: 26

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