drop_constants: Drop constant variables from a formula

In MoEClust: Gaussian Parsimonious Clustering Models with Covariates and a Noise Component

Drop constant variables from a formula

Description

Drops constant variables from the RHS of a formula taking the data set (dat), the formula (formula), and an optional subset vector (sub) as arguments.

Usage

drop_constants(dat,
               formula,
               sub = NULL)

Arguments

dat	A data.frame where rows correspond to observations and columns correspond to variables. Ideally column names should be present.
formula	An object of class "formula": a symbolic description of the model to be fitted. Variables in the formula not present in the columns of dat will automatically be discarded. The formula may include interactions, transformations, or higher order terms: the latter must be specified explicitly using the AsIs operator (I).
sub	An optional vector specifying a subset of observations to be used in the fitting process.

Value

The updated formula with constant variables removed.

Note

Formulas with and without intercepts are accommodated.

Author(s)

Keefe Murphy - <[e-mail]>

See Also

drop_levels, I

Examples

data(ais)
hema  <- as.matrix(ais[,3:7])
sex   <- ais$sex
BMI   <- ais$BMI

# Set up a no-intercept regression formula with constant column 'sex'
form1 <- as.formula(hema ~ sex + BMI + I(BMI^2) - 1)
sub   <- ais$sex == "male"

# Try fitting a linear model
mod1  <- try(lm(form1, data=ais, subset=sub), silent=TRUE)
inherits(mod1, "try-error") # TRUE

# Remove redundant variables from formula & try again
form2 <- drop_constants(ais, form1, sub)
mod2  <- try(lm(form2, data=ais, subset=sub), silent=TRUE)
inherits(mod2, "try-error") # FALSE

MoEClust documentation built on Dec. 28, 2022, 2:24 a.m.