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Ordinal regression via polr

Source: R/ordinal_reg_polr.R
details_ordinal_reg_polr.Rd

MASS::polr() fits a cumulative-link ordinal regression model.

Details

For this engine, there is a single mode: classification

Tuning Parameters

This model has no tuning parameters.

Translation from parsnip to the original package

The ordered extension package is required to fit this model.

library(ordered)

ordinal_reg() %>%
  set_engine("polr") %>%
  set_mode("classification") %>%
  translate()

## Ordinal Regression Model Specification (classification)
##
## Computational engine: polr
##
## Model fit template:
## MASS::polr(formula = missing_arg(), data = missing_arg(), weights = missing_arg())

Prediction types

parsnip:::get_from_env("ordinal_reg_predict") |>
  dplyr::filter(engine == "polr") |>
  dplyr::select(mode, type)

## # A tibble: 2 x 2
##   mode           type
##   <chr>          <chr>
## 1 classification class
## 2 classification prob

References

  • Bürkner P-C, Vuorre M. 2019. Ordinal Regression Models in Psychology: A Tutorial. Advances in Methods and Practices in Psychological Science 2(1):77-101. .