compare_to_target {PriceIndices}

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 = TRUE,
  prec = 3
)

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.

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).

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)