Hi,

I'm trying to build a parsnip model for the nlme::gls function following steps available at Learn - How to build a parsnip model. When I test the built model again Ovary dataset (associated to nlme package) I got the error message 'unused formula argument' (see reproducible code below). My understanding is that nlme::gls argument for formula is 'model' (see ?gls) and not formula. I tried to modify using set_model_arg(parsnip = "formula", original = "model"), but it didn't help.

Happy and grateful for any support!

Kevin

```
library(tidymodels)
#> Warning: package 'tidymodels' was built under R version 4.0.5
#> Registered S3 method overwritten by 'tune':
#> method from
#> required_pkgs.model_spec parsnip
#> Warning: package 'broom' was built under R version 4.0.5
#> Warning: package 'dials' was built under R version 4.0.5
#> Warning: package 'dplyr' was built under R version 4.0.5
#> Warning: package 'ggplot2' was built under R version 4.0.5
#> Warning: package 'infer' was built under R version 4.0.5
#> Warning: package 'parsnip' was built under R version 4.0.5
#> Warning: package 'recipes' was built under R version 4.0.5
#> Warning: package 'rsample' was built under R version 4.0.5
#> Warning: package 'tibble' was built under R version 4.0.4
#> Warning: package 'tidyr' was built under R version 4.0.5
#> Warning: package 'tune' was built under R version 4.0.5
#> Warning: package 'workflows' was built under R version 4.0.5
#> Warning: package 'workflowsets' was built under R version 4.0.5
#> Warning: package 'yardstick' was built under R version 4.0.5
library(nlme)
#>
#> Attaching package: 'nlme'
#> The following object is masked from 'package:dplyr':
#>
#> collapse
set_new_model("gls_tidy")
set_model_mode(model = "gls_tidy", mode = "regression")
set_model_engine(
"gls_tidy",
mode = "regression",
eng = "gls"
)
set_dependency("gls_tidy", eng = "gls", pkg = "nlme")
set_model_arg(
model = "gls_tidy",
eng = "gls",
parsnip = "correlation",
original = "correlation",
func = list(pkg = "nlme", fun = "bar"),
has_submodel = FALSE
)
set_model_arg(
model = "gls_tidy",
eng = "gls",
parsnip = "formula",
original = "model",
func = list(pkg = "nlme", fun = "gls"),
has_submodel = FALSE
)
show_model_info("gls_tidy")
#> Information for `gls_tidy`
#> modes: unknown, regression
#>
#> engines:
#> regression: gls
#>
#> arguments:
#> gls:
#> correlation --> correlation
#> formula --> model
#>
#> no registered fit modules.
#>
#> no registered prediction modules.
gls_tidy <-
function(mode = "regression", model=NULL, correlation = NULL) {
# Check for correct mode
if (mode != "regression") {
rlang::abort("`mode` should be 'regression'")
}
# Capture the arguments in quosures
args <- list(correlation = rlang::enquo(correlation))
# Save some empty slots for future parts of the specification
new_model_spec(
"gls_tidy",
args = args,
eng_args = NULL,
mode = mode,
method = NULL,
engine = NULL
)
}
set_fit(
model = "gls_tidy",
eng = "gls",
mode = "regression",
value = list(
interface = "formula",
protect = c("formula", "data"),
func = c(pkg = "nlme", fun = "gls"),
defaults = list()
)
)
set_encoding(
model = "gls_tidy",
eng = "gls",
mode = "regression",
options = list(
predictor_indicators = "traditional",
compute_intercept = TRUE,
remove_intercept = TRUE,
allow_sparse_x = FALSE
)
)
show_model_info("gls_tidy")
#> Information for `gls_tidy`
#> modes: unknown, regression
#>
#> engines:
#> regression: gls
#>
#> arguments:
#> gls:
#> correlation --> correlation
#> formula --> model
#>
#> fit modules:
#> engine mode
#> gls regression
#>
#> no registered prediction modules.
gls_tidy(model=NULL,correlation = corGaus(1, form = ~ x + y)) %>%
translate(engine = "gls")
#> Model Specification (regression)
#>
#> Main Arguments:
#> correlation = corGaus(1, form = ~x + y)
#>
#> Computational engine: gls
#>
#> Model fit template:
#> nlme::gls(formula = missing_arg(), data = missing_arg(), correlation = corGaus(1,
#> form = ~x + y))
gls_spec <- gls_tidy(correlation = corGaus(1, form = ~ x + y)) %>%
set_engine("gls")
gls_fit <- gls_spec %>%
fit(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), data = Ovary, engine = "gls")
#> Error in nlme::gls(formula = follicles ~ sin(2 * pi * Time) + cos(2 * : unused argument (formula = follicles ~ sin(2 * pi * Time) + cos(2 * pi * Time))
#> Timing stopped at: 0 0 0
```

Created on 2021-08-26 by the reprex package (v2.0.1)