Estimate hpi models with hed approach
# S3 method for hed
hpiModel(model_type, hpi_df, estimator = "base",
log_dep = TRUE, trim_model = TRUE, mod_spec = NULL,
dep_var = NULL, ind_var = NULL, ...)Type of model to estimate ('rt', 'hed', 'rf')
Dataset created by one of the *CreateSales() function in this package.
Type of estimator to be used ('base', 'weighted', 'robust')
default=TRUE; should the dependent variable (change in price) be logged?
default TRUE, should excess be trimmed from model results ('lm' or 'rlm' object)?
default=NULL; hedonic model specification
default=NULL; dependent variable of the model
default=NULL; independent variable(s) of the model
Additional Arguments
hpimodel object consisting of:
Type of estimator
Data.frame of coefficient
class `rtmodel` or `hedmodel`
Full model specification
Binary: is the dependent variable in logged format
Mean price in the base period
`data.frame` of periods
Type of model used