qNormalise.purse {COINr} | R Documentation |
Quick normalisation of a purse
Description
This is a wrapper function for Normalise()
, which offers a simpler syntax but less flexibility. It
normalises data sets within a purse using a specified function f_n
which is used to normalise each indicator, with
additional function arguments passed by f_n_para
. By default, f_n = "n_minmax"
and f_n_para
is
set so that the indicators are normalised using the min-max method, between 0 and 100.
Usage
## S3 method for class 'purse'
qNormalise(
x,
dset,
f_n = "n_minmax",
f_n_para = list(l_u = c(0, 100)),
directions = NULL,
global = TRUE,
...
)
Arguments
x |
A purse |
dset |
Name of data set to normalise |
f_n |
Name of a normalisation function (as a string) to apply to each indicator. Default |
f_n_para |
Any further arguments to pass to |
directions |
An optional data frame containing the following columns:
|
global |
Logical: if |
... |
arguments passed to or from other methods. |
Details
Essentially, this function is similar to Normalise()
but brings parameters into the function arguments
rather than being wrapped in a list. It also does not allow individual normalisation.
Normalisation can either be performed independently on each coin, or over the entire panel data set
simultaneously. See the discussion in Normalise.purse()
and vignette("normalise")
.
Value
An updated purse with normalised data sets
Examples
# build example purse
purse <- build_example_purse(up_to = "new_coin", quietly = TRUE)
# normalise using min-max, globally
purse <- qNormalise(purse, dset = "Raw", global = TRUE)