I am responding to a subset of what you asked. There are packages which use
multiple formulas
in their argument sequence.
What you have as a single formula with | as a separator
q | p | subject | time | rho ~ p + x + y | p + w + y | z + y
I think would be better as a comma-separated list of formulas
q , p , subject , time , rho ~ p + x + y , p + w + y , z + y
because in R notation | is usually an operator, not a separator.
lattice uses formulas and the | is used as a conditioning operator.
nlme and lme4 can have multiple formulas in the same calling sequence.
lme4 is newer. from its ?lme4-package
‘lme4’ covers approximately the same ground as the earlier ‘nlme’
package.
lme4 should probably be the modelyou are looking for for the package design.
> On Oct 07, 2021, at 17:20, pikappa.de...@gmail.com wrote:
>
> Dear R-package-devel subscribers,
>
>
>
> My question concerns a package design issue relating to the usage of
> formulas.
>
>
>
> I am interested in describing via formulas systems of the form:
>
>
>
> d = p + x + y
>
> s = p + w + y
>
> p = z + y
>
> q = min(d,s).
>
>
>
> The context in which I am working is that of market models with, primarily,
> panel data. In the above system, one may think of the first equation as
> demand, the second as supply, and the third as an equation (co-)determining
> prices. The fourth equation is implicitly used by the estimation method, and
> it does not need to be specified when programming the R formula. If you need
> more information bout the system, you may check the package diseq.
> Currently, I am using constructors to build market model objects. In a
> constructor call, I pass [i] the right-hand sides of the first three
> equations as strings, [ii] an argument indicating whether the equations of
> the system have correlated shocks, [iii] the identifiers of the used dataset
> (one for the subjects of the panel and one for time), and [iv] the quantity
> (q) and price (p) variables. These four arguments contain all the necessary
> information for constructing a model.
>
>
>
> I would now like to re-implement model construction using formulas, which
> would be a more regular practice for most R users. I am currently
> considering passing all the above information with a single formula of the
> form:
>
>
>
> q | p | subject | time | rho ~ p + x + y | p + w + y | z + y
>
>
>
> where subject and time are the identifiers, and rho indicates whether
> correlated or independent shocks should be used.
>
>
>
> I am unaware of other packages that use formulas in this way (for instance,
> passing the identifiers in the formula), and I wonder if this would go
> against any good practices. Would it be better to exclude some of the
> necessary elements for constructing the model? This might make the resuting
> formulas more similar to those of models with multiple responses or multiple
> parts. I am not sure, though, how one would use such model formulas without
> all the relevant information. Is there any suggested design alternative that
> I could check?
>
>
>
> I would appreciate any suggestions and discussion!
>
>
>
> Kind regards,
>
> Pantelis
>
>
> [[alternative HTML version deleted]]
>
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