hpiR (version 0.2.0)

hpiModel: Wrapper to estimate model approaches (generic method)

Description

Generic method to estimate modeling approaches for indexes

Usage

hpiModel(hpi_df, estimator = "base", log_dep = TRUE, trim_model = TRUE,
  ...)

Arguments

hpi_df

Dataset created by one of the *CreateTrans() function in this package.

estimator

Type of estimator to be used ('base', 'weighted', 'robust')

log_dep

default TRUE, should the dependent variable (change in price) be logged?

trim_model

default TRUE, should excess be trimmed from model results ('lm' or 'rlm' object)?

...

Additional Arguments

Value

hpimodel object consisting of:

estimator

Type of estimator

coefficients

Data.frame of coefficient

model_obj

class `rtmodel` or `hedmodel`

mod_spec

Full model specification

log_dep

Binary: is the dependent variable in logged format

base_price

Mean price in the base period

periods

`data.frame` of periods

approach

Type of model used

Examples

Run this code
# NOT RUN {
 # Load data
 data(ex_sales)

 # With a raw transaction data.frame
 rt_data <- rtCreateTrans(trans_df = ex_sales,
                          prop_id = 'pinx',
                          trans_id = 'sale_id',
                          price = 'sale_price',
                          periodicity = 'monthly',
                          date = 'sale_date')

 # Create model object
 hpi_model <- hpiModel(hpi_df = rt_data,
                       estimator = 'base',
                       log_dep = TRUE)

# }

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