grautur - 1 month ago 7

R Question

Suppose I have a response variable and a data containing three covariates (as a toy example):

`y = c(1,4,6)`

d = data.frame(x1 = c(4,-1,3), x2 = c(3,9,8), x3 = c(4,-4,-2))

I want to fit a linear regression to the data:

`fit = lm(y ~ d$x1 + d$x2 + d$y2)`

Is there a way to write the formula, so that I don't have to write out each individual covariate? For example, something like

`fit = lm(y ~ d)`

(I want each variable in the data frame to be a covariate.) I'm asking because I actually have 50 variables in my data frame, so I want to avoid writing out

`x1 + x2 + x3 + etc`

Answer

There is a special identifier that one can use in a formula to mean all the variables, it is the `.`

identifier.

```
y <- c(1,4,6)
d <- data.frame(y = y, x1 = c(4,-1,3), x2 = c(3,9,8), x3 = c(4,-4,-2))
mod <- lm(y ~ ., data = d)
```

You can also do things like this, to use all variables bar one:

```
mod <- lm(y ~ . - x3, data = d)
```

Technically, `.`

means *all variables not already mentioned in the formula*. For example

```
lm(y ~ x1 * x2 + ., data = d)
```

where `.`

would only reference `x3`

as `x1`

and `x2`

are already in the formula.

Source (Stackoverflow)

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