performance
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test_performance for GAMMs
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Will try to look into this when I have time:
model1 <- mgcv::gamm(Sepal.Length ~ s(Petal.Width), random=list(Species = ~1), data=iris, family=inverse.gaussian(link = "identity"))
#>
#> Maximum number of PQL iterations: 20
#> iteration 1
#> iteration 2
#> iteration 3
model2 <- lme4::glmer(Sepal.Length ~ poly(Sepal.Width, 2) + (1|Species), data=iris, family=inverse.gaussian(link = "identity"))
model3 <- gamm4::gamm4(Sepal.Length ~ s(Petal.Width), random=~(1|Species), data=iris, family=inverse.gaussian(link = "identity"))
performance::test_performance(model1, model2)
#> Name | Model.model1 | Model.model2
#> ------------------------------------
#> model1 | lme | glmerMod
#> model2 | gam | glmerMod
#> Models were detected as nested and are compared in sequential order.
performance::test_performance(model1, model3)
#> Warning: Unable to extract terms from the following models:
#> model3
#> Name | Model.model1 | Model.model3
#> ------------------------------------
#> model1 | lme | glmerMod
#> model3 | gam | gam
#> Models were detected as nested and are compared in sequential order.
performance::test_performance(model2, model3)
#> Warning: Unable to extract terms from the following models:
#> model3
#> Name | Model.model2 | Model.model3
#> ------------------------------------
#> model2 | glmerMod | glmerMod
#> model3 | glmerMod | gam
#> Each model is compared to model2.
Created on 2021-02-20 by the reprex package (v0.3.0)
I was just about to submit an issue about something similar. Out of curiosity, are there any plans regarding making check_model amicable to mgcv::gam models?