Description Usage Arguments Details Value Examples
This function tries to choose sensible values of the explanatory variables
from the data used to build a model or any other specified data.
(or from data specified with the data =
argument.)
1 |
model |
the model to display graphically |
data |
optional data frame from which to extract levels for explanatory variables |
nlevels |
how many levels to construct for input variables.
For quantitative variables, this is a suggestion. |
at |
named list giving specific values at which to hold the variables. Use this to override the automatic generation of levels for any or all explanatory variables. |
... |
a more concise mechanism to passing desired values for variables |
For categorical variables, the most populated levels are used. For quantitative
variables, a sequence of pretty()
values is generated.
A dataframe containing all combinations of the selected values for
the explanatory variables. If there are p explanatory variables,
there will be about nlevels^p
cases.
1 2 3 4 5 6 7 | ## Not run: mod1 <- lm(wage ~ age * sex + sector, data = mosaicData::CPS85)
typical_levels(mod1)
mod3 <- glm(married == "Married" ~ age + sex * sector,
data = mosaicData::CPS85, family = "binomial")
typical_levels(mod3, nlevels = 2)
## End(Not run)
|
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