calcAccuracy {hpiR}

Calculate the accuracy of an index

Description

Estimate index accuracy using one of a variety of approaches

Usage

calcAccuracy(hpi_obj, test_method = "insample", test_type = "rt",
  pred_df = NULL, smooth = FALSE, in_place = FALSE,
  in_place_name = "accuracy", ...)

Arguments

hpi_obj

Object of class 'hpi'

test_method

default = 'insample'; Also 'kfold'

test_type

default = 'rt'; Type of data to use for test. See details.

pred_df

default = NULL; Extra data if the test_type doesn't match data in hpi_obj

smooth

default = FALSE; calculated on the smoothed index(es)

in_place

default = FALSE; Should the result be returned into an existing 'hpi' object

in_place_name

default = 'accuracy'; Name for returning in place

...

Additional Arguments

Value

object of class 'hpiaccuracy' inheriting from class 'data.frame' containing the following fields:

prop_id

Property Identification number

price

Transaction Price

pred_price

Predicted price

error

(Prediction - Actual) / Actual

log_error

log(prediction) - log(actual)

pred_period

Period of the prediction

Further Details

'rt' test type tests the ability of the index to correctly predict the second value in a repeat transaction pair FUTURE: 'hed' test type tests the ability of the index to improve an OLS model that doesn't account for time. (This approach is not ready yet).

Examples

 # Load Data
 data(ex_sales)

 # Create Index
 rt_index <- rtIndex(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 = 'robust',
                     log_dep = TRUE,
                     trim_model = TRUE,
                     max_period = 48,
                     smooth = FALSE)

 # Calculate insample accuracy
 hpi_accr <- calcAccuracy(hpi_obj = rt_index,
                          test_type = 'rt',
                          test_method = 'insample')