Comments (2)
Hello, it seems that models of class gamm
are not supported by the package report
(as indicated in the message). However, it is possible to run performance::performance()
on them:
library(mgcv)
#> Le chargement a nécessité le package : nlme
#> This is mgcv 1.9-0. For overview type 'help("mgcv-package")'.
packageVersion("performance")
#> [1] '0.10.4'
packageVersion("report")
#> [1] '0.5.7.10'
# from mgcv::gamm
set.seed(0)
dat <- gamSim(1,n=200,scale=2)
#> Gu & Wahba 4 term additive model
model <- gamm(y~s(x0)+s(x1)+s(x2)+s(x3),data=dat)
performance::performance(model)
#> Warning in nobs.default(object, use.fallback = use.fallback): pas de méthode
#> 'nobs' disponible
#> # Indices of model performance
#>
#> AIC | BIC | R2 | RMSE | Sigma
#> -----------------------------------------
#> 891.170 | 940.654 | 0.707 | 2.083 | 2.115
report::report_performance(model)
#> Error: Oops, objects of class [gamm, list] are not supported (yet) by report_performance() :(
#>
#> Want to help? Check out https://easystats.github.io/report/articles/new_models.html
Therefore I move this issue to the report
repository (also next time please use a more explicit title than "please!")
from report.
Many thanks Etienne, and sorry for the unexplicit title. It was just my frustration speaking.
Great work!
Irene
from report.
Related Issues (20)
- Failures with devel-easystats HOT 2
- ESS is reported inconsistently for `brmsfit` objects HOT 3
- Failing tests: Persistent error in pak subprocess HOT 1
- README example not working HOT 1
- Support Fisher exact test reporting HOT 2
- pkgdown website HOT 4
- Feature request: Add `n_Obs` column to `htest` summary outputs, etc.
- cannot do report for lm() now HOT 1
- automated reporting of interactions or pairwise tests HOT 5
- Add report support for `modelbased::estimate_contrasts`
- objects of class [Date] are not supported by report_table() HOT 7
- Report brms refitting models HOT 7
- report dataset with date 0.5.8 good news but how to install HOT 6
- Grouped `report_participants()` does not report gender unless argument `gender` is capitalized
- `report.lm`: "Warning: Using `$` in model formulas can produce unexpected results", but doing so errors HOT 3
- Unclear reporting HOT 1
- The model's explanatory power is "substantial" HOT 1
- What's the best way to provide appropriate attribution/citation? HOT 2
- emmeans and beta regression support
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