Can I mix symbolic terms (eg. factor) and objects (eg. matrix) in an R formula?

I would like to specify a list of components using the R formula interface. For example:

~ component1 + component2 + component3

If all the components are (functions of) columns in a data frame, this is straightforward. However, I want to be able to specify components of different type (eg. a sparse matrix).

Here is an approach using model.frame that works for factor and matrix objects:

nobs <- nrow(mtcars)

Vformula <- ~ factor(cyl) + diag(nobs)

V <- model.frame(Vformula, data = mtcars)
V <- as.list(V)

V[[1]]
#>  [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4
#> Levels: 4 6 8
V[[2]][1:6, 1:6]
#>      [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,]    1    0    0    0    0    0
#> [2,]    0    1    0    0    0    0
#> [3,]    0    0    1    0    0    0
#> [4,]    0    0    0    1    0    0
#> [5,]    0    0    0    0    1    0
#> [6,]    0    0    0    0    0    1

However, model.frame throws an error if one of the components is a sparse matrix (of class Matrix::ddiMatrix).

library("Matrix")

Vformula <- ~ factor(cyl) + Diagonal(nobs)

V <- model.frame(Vformula, data = data, na.action = na.pass)
#> Error in model.frame.default(Vformula, data = data, na.action = na.pass): 'data' must be a data.frame, environment, or list

The objective is to come up with a convenient way to pass these components as input to a function that can then process them differently depending on whether V[[i]] is a symbolic term or a sparse matrix.

^{Created on 2024-06-09 with reprex v2.1.0}