# ðŸ“Š R - *Formula Objects*

*Formula Objects*

Updated at 2017-10-16 19:59

**Formulae convey a relationship among a set of variables.** We can define a formula without having any data loaded.

```
~ x
# formula that defines a single independent variable, "x", pretty useless
y ~ x
# one dependent variable, translates to "y" depends on "x".
```

** ~ creates a formula object.** They are used differently by different libraries, but the original intent was to allow specify "which variables does the left side depend on?"

```
# left of ~ is the dependent variable, the "outcome" or "result"
# right of ~ are the independent/predictor/covariate variables
myFormula <- Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width
myFormula
# Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width
# you would read this as "Species depends on Sepal.Length, Sepal.Width..."
allFormula <- Species ~ .
allFormula
# Species ~ .
# . in formula translates to "all variables not yet used"
# you would read this as "Species depends on all the other variables."
```

- An expression of
`y ~ model`

is interpreted as the response`y`

is modeled by a predictor specified symbolically by`model`

. `+`

operator is used to separate terms in a model.`:`

operator is used to separate variable and factor names in those terms.`*`

operator denotes factor crossing:`a*b`

interpreted as`a+b+a:b`

.`^`

operator indicates crossing to the specified degree:`(a+b+c)^2`

is identical to`(a+b+c)*(a+b+c)`

.`%in%`

operator indicates that the terms on its left are nested within those on the right:`a + b %in% a`

expands to the formula`a + a:b`

`-`

operator removes the specified terms:`(a+b+c)^2 - a:b`

is identical to`a + b + c + b:c + a:c`

.