PriceIndices (version 0.2.3)

compare_to_target: Calculating distances between considered price indices and the target price index

Description

The function calculates distances between considered price indices and the target price index

Usage

compare_to_target(
  data = data.frame(),
  target,
  measure = "MAD",
  pp = TRUE,
  first = FALSE,
  prec = 3
)

Value

The function calculates average distances between considered price indices and the target price index and it returns a data frame with: average distances on the basis of all values of compared indices ('distance' column), average semi-distances on the basis of values of compared indices which overestimate the target index values ('distance_upper' column) and average semi-distances on the basis of values of compared indices which underestimate the target index values ('distance_lower' column).

Arguments

data

A data frame containg values of indices which are to be compared to the target price index

target

A data frame or a vector containg values of the target price index

measure

A parameter specifying what measure should be used to compare indices. Possible parameter values are: "MAD" (Mean Absolute Distance) or "RMSD" (Root Mean Square Distance).

pp

Logical parameter indicating whether the results are to be presented in percentage points (then pp = TRUE).

first

A logical parameter that determines whether the first row of the data frame and the first row of the 'target' data frame (or its first element if it is a vector) are to be taken into account when calculating the distance between the indices (then first = TRUE). Usually, the first row concerns the index values for the base period - all indexes are then set to one.

prec

Parameter that determines how many decimal places are to be used in the presentation of results.

Examples

#Creating a data frame with example bilateral indices
df<-price_indices(milk, 
formula=c("jevons","laspeyres","paasche","walsh"),
start="2018-12",end="2019-12",interval=TRUE)
#Calculating the target Fisher price index
target_index<-fisher(milk,start="2018-12",end="2019-12",interval=TRUE)
#Calculating average distances between considered indices and the Fisher index (in p.p)
compare_to_target(df,target=target_index)