rfIndex: Create a full index object by random forest approach

In hpiR: House Price Indexes

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

 # 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)

hpiR documentation built on April 1, 2020, 5:09 p.m.