R/df_typical.R
df_typical.Rd
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.)
df_typical(data = NULL, nlevels = 3, at = list(), model = NULL, ...)
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. Set to |
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. |
model | the model to display graphically |
... | a more concise mechanism to passing desired values for variables |
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.
For categorical variables, the most populated levels are used. For quantitative
variables, a sequence of pretty()
values is generated.
For categorical variables, will return the nlevels most popular levels, unless the levels are specified explicitly in an argument.
# NOT RUN { df_typical(mosaicData::Galton, nlevels = 2, father = 70, mother = 68, nkids = 3) df_typical(mosaicData::Galton, nlevels = 2) mod1 <- lm(wage ~ age * sex + sector, data = mosaicData::CPS85) df_typical(model = mod1, nlevels = 3) # }