A FixedEffectsSet represents a group of fixed-effects models that all have
the same functional structure. Fitting a large family of models (e.g., for
many different species) using the same functional structure is a common
pattern in allometric studies, and FixedEffectsSet facilitates the
installation of these groups of models by allowing the user to specify the
parameter estimates and descriptions in a dataframe.
A named list containing one element, with a name representing the response
variable and a value representing the units of the response variable
using the units::as_units function.
A named list containing the covariate specifications, with names
representing the covariate name and the values representing the units of
the coavariate using the units::as_units function
A character vector naming the columns in model_specifications that
represent the parameters
A function that takes the covariate names as arguments and returns a prediction of the response variable. This function should be vectorized.
A dataframe such that each row of the dataframe provides model-level
descriptors and parameter estimates for that model. Models must be
uniquely identifiable using the descriptors. This is usually established
using the load_parameter_frame() function.
An optional named list of descriptors that describe the context of the allometric model
A string containing an optional custom response definition, which is used instead of the description given by the variable naming system.
An optional named list of custom covariate definitions that will supersede
the definitions given by the variable naming system. The names of the list
must match the covariate names given in covariates.
A set of fixed effects models
response_unitA one-element list with the name indicating the response
variable and the value as the response variable units obtained using
units::as_units()
covariate_unitsA list containing the covariate names as names and
values as the values of the covariate units obtained using
units::as_units()
predict_fnThe prediction function, which takes covariates as arguments and returns model predictions
descriptorsA tibble::tbl_df containing the model descriptors
set_descriptorsA tibble::tbl_df containing the set descriptors
pub_descriptorsA tibble::tbl_df containing the publication
descriptors
citationA RefManageR::BibEntry object containing the reference
publication
covariate_definitionsUser-provided covariate definitions
model_typeThe model type, which is parsed from the response_unit
name
parameter_namesA character vector indicating the parameter names
model_specificationsA tibble::tbl_df of model specifications, where
each row reprents one model identified with descriptors and containing the
parameter estimates.