Create a fixed effects model — FixedEffectsModel • allometric

FixedEffectsModel represents an allometric model that only uses fixed effects.

FixedEffectsModel(
  response,
  covariates,
  predict_fn,
  parameters,
  descriptors = list(),
  response_definition = NA_character_,
  covariate_definitions = list()
)

Arguments

response: 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.
covariates: 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
predict_fn: A function that takes the covariate names as arguments and returns a prediction of the response variable. This function should be vectorized.
parameters: A named list of parameters and their values
descriptors: An optional named list of descriptors that describe the context of the allometric model
response_definition: A string containing an optional custom response definition, which is used instead of the description given by the variable naming system.
covariate_definitions: 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.

Value

An object of class FixedEffectsModel

Slots

response_unit: A one-element list with the name indicating the response variable and the value as the response variable units obtained using units::as_units()
covariate_units: A list containing the covariate names as names and values as the values of the covariate units obtained using units::as_units()
predict_fn: The prediction function, which takes covariates as arguments and returns model predictions
descriptors: A tibble::tbl_df containing the model descriptors
set_descriptors: A tibble::tbl_df containing the set descriptors
pub_descriptors: A tibble::tbl_df containing the publication descriptors
citation: A RefManageR::BibEntry object containing the reference publication
covariate_definitions: User-provided covariate definitions
model_type: The model type, which is parsed from the response_unit name
parameters: A named list of parameters and their values
predict_fn_populated: The prediction function populated with the parameter values
specification: A tibble::tbl_df of the model specification, which are the parameters and the descriptors together

Examples

FixedEffectsModel(
  response = list(
    hst = units::as_units("m")
  ),
  covariates = list(
    dsob = units::as_units("cm")
  ),
  parameters = list(
    beta_0 = 51.9954,
    beta_1 = -0.0208,
    beta_2 = 1.0182
  ),
  predict_fn = function(dsob) {
    1.37 + beta_0 * (1 - exp(beta_1 * dsob)^beta_2)
  }
)
#> Model Call: 
#> hst = f(dsob) 
#>  
#> hst [m]: total height of the stem
#> dsob [cm]: diameter of the stem, outside bark at breast height 
#> 
#> Parameter Estimates: 
#> # A tibble: 1 × 3
#>   beta_0  beta_1 beta_2
#>    <dbl>   <dbl>  <dbl>
#> 1   52.0 -0.0208   1.02
#> 
#> Model Descriptors: 
#> # A tibble: 1 × 0