Proportional hazards regressionSource:
proportional_hazards() defines a model for the hazard function
as a multiplicative function of covariates times a baseline hazard. This
function can fit censored regression models.
There are different ways to fit this model, and the method of estimation is chosen by setting the model engine. The engine-specific pages for this model are listed below.
More information on how parsnip is used for modeling is at https://www.tidymodels.org/.
proportional_hazards( mode = "censored regression", engine = "survival", penalty = NULL, mixture = NULL )
A single character string for the prediction outcome mode. The only possible value for this model is "censored regression".
A single character string specifying what computational engine to use for fitting.
A non-negative number representing the total amount of regularization (specific engines only).
A number between zero and one (inclusive) denoting the proportion of L1 regularization (i.e. lasso) in the model.
mixture = 1specifies a pure lasso model,
mixture = 0specifies a ridge regression model, and
0 < mixture < 1specifies an elastic net model, interpolating lasso and ridge.
Available for specific engines only.
This function only defines what type of model is being fit. Once an engine
is specified, the method to fit the model is also defined. See
set_engine() for more on setting the engine, including how to set engine
The model is not trained or fit until the
fit() function is used
with the data.
value <- 1 proportional_hazards(argument = !!value)
Since survival models typically involve censoring (and require the use of
survival::Surv() objects), the
fit.model_spec() function will require that the
survival model be specified via the formula interface.
Proportional hazards models include the Cox model.
show_engines("proportional_hazards") #> # A tibble: 0 × 2 #> # ℹ 2 variables: engine <chr>, mode <chr> proportional_hazards(mode = "censored regression") #> ! parsnip could not locate an implementation for `proportional_hazards` #> censored regression model specifications. #> ℹ The parsnip extension package censored implements support for this #> specification. #> ℹ Please install (if needed) and load to continue. #> Proportional Hazards Model Specification (censored regression) #> #> Computational engine: survival #>