hpiR (version 0.3.2)

rfIndex: Create a full index object by random forest approach

Description

Wrapper to create index object via entire random forest approach

Usage

rfIndex(trans_df, dep_var = NULL, ind_var = NULL, rf_spec = NULL,
  ...)

Arguments

trans_df

data.frame of transactions

dep_var

default = NULL; Dependent variable in hedonic model

ind_var

default = NULL; Independent variables in the hedonic model

rf_spec

default = NULL; Full random forest model specification

...

Additional Arguments

Value

`hpi`` object. S3 list with:

data

`hpidata` object

model

`hpimodel` object

index

`hpiindex` object

Further Details

Additional argument need to provide necessary argument for create `hpidata` objects if the `trans_df` object is not of that class.

Examples

# NOT RUN {

 # Load data
 data(ex_sales)

 # Create index with raw transaction data
 rf_index <- rfIndex(trans_df = ex_sales,
                     periodicity = 'monthly',
                     min_date = '2010-06-01',
                     max_date = '2015-11-30',
                     adj_type = 'clip',
                     date = 'sale_date',
                     price = 'sale_price',
                     trans_id = 'sale_id',
                     prop_id = 'pinx',
                     estimator = 'pdp',
                     log_dep = TRUE,
                     trim_model = TRUE,
                     max_period = 48,
                     dep_var = 'price',
                     ind_var = c('tot_sf', 'beds', 'baths'),
                     smooth = FALSE,
                     ntrees = 10,
                     sim_count = 2)

# }