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It would be very useful if glmmTMB supported different types of ordinal regression, e.g. the proportional odds model (cumulative link logit model).
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I think that a major missing gap in parsnip is explicit support for ordinal models, by which I mean **models where the response variable is an ordered factor**.
My proposal here is a follow up to […
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Recently, [Sakai (2021)](https://aclanthology.org/2021.acl-long.214) compared several class, numeric, and proposed "ordinal" performance measures/metrics on ordinal classification tasks. This raises t…
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To authors of this publication,
For a final group project in my statistics course, we chose to replicate your regression analyses. I am curious as to why you have an ordered logistic regression inc…
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Prof. Raschka had an idea of prioritizing clusters instead of individual compounds. His idea was to use ordinal regression to predict the number of actives in the cluster. This would require featuri…
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Both `binomial()` and `poisson()` families in `stats::family` have a fixed dispersion parameter at one. It appears that dispersion is relaxed to vary in Poisson regression through `compois()` and `ge…
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Wonderful package!
Can this package/framework also be used to model ordinal outcomes (i.e., without treating Y as nominal or continuous) to model cumulative probabilities, like Pr(Y
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Hi,
I have a task where my class types are ordinal and I am using the code provided here. But the performance after adding this param worsens, I wanted to know if my understanding of the params is …
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#### Describe the workflow you want to enable
If the target is discrete multiclass, but ordinal (ordered) in nature (e.g. Likert scale, user ratings, preference levels), as opposed to nominal, wo…
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### JASP Version
0.19.0
### Commit ID
_No response_
### JASP Module
Regression
### What analysis are you seeing the problem on?
Generalized Linear Model > Family = Other > Model = Multinomial L…
patc3 updated
2 months ago