Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
# numbers between 1 and 10
x <- 1:10
# two outliers
x <- c(x, 30, 100)
## -----------------------------------------------------------------------------
library(COINr)
skew(x)
kurt(x)
## -----------------------------------------------------------------------------
check_SkewKurt(x)
## ---- fig.width=5, fig.height=3.5---------------------------------------------
l_treat <- Treat(x, f1 = "winsorise", f1_para = list(winmax = 2),
f_pass = "check_SkewKurt")
plot(x, l_treat$x)
## -----------------------------------------------------------------------------
check_SkewKurt(l_treat$x)
## -----------------------------------------------------------------------------
# select three indicators
df1 <- ASEM_iData[c("Flights", "Goods", "Services")]
# treat the data frame using defaults
l_treat <- Treat(df1)
str(l_treat, max.level = 1)
## -----------------------------------------------------------------------------
l_treat$Dets_Table
## -----------------------------------------------------------------------------
l_treat$Treated_Points
## -----------------------------------------------------------------------------
coin <- build_example_coin(up_to = "new_coin")
## -----------------------------------------------------------------------------
coin <- Treat(coin, dset = "Raw")
## -----------------------------------------------------------------------------
# summary of treatment for each indicator
head(coin$Analysis$Treated$Dets_Table)
## -----------------------------------------------------------------------------
# default treatment for all cols
specs_def <- list(f1 = "winsorise",
f1_para = list(na.rm = TRUE,
winmax = 5,
skew_thresh = 2,
kurt_thresh = 3.5,
force_win = FALSE),
f2 = "log_CT",
f2_para = list(na.rm = TRUE),
f_pass = "check_SkewKurt",
f_pass_para = list(na.rm = TRUE,
skew_thresh = 2,
kurt_thresh = 3.5))
## -----------------------------------------------------------------------------
# treat with max winsorisation of 3 points
coin <- Treat(coin, dset = "Raw", global_specs = list(f1_para = list(winmax = 1)))
# see what happened
coin$Analysis$Treated$Dets_Table |>
head(10)
## -----------------------------------------------------------------------------
# change individual specs for Flights
indiv_specs <- list(
Flights = list(
f1_para = list(winmax = 0)
)
)
# re-run data treatment
coin <- Treat(coin, dset = "Raw", indiv_specs = indiv_specs)
## -----------------------------------------------------------------------------
coin$Analysis$Treated$Dets_Table[
coin$Analysis$Treated$Dets_Table$iCode == "Flights",
]
## -----------------------------------------------------------------------------
# change individual specs for two indicators
indiv_specs <- list(
Flights = "none",
LPI = "none"
)
# re-run data treatment
coin <- Treat(coin, dset = "Raw", indiv_specs = indiv_specs)
## ---- include = FALSE---------------------------------------------------------
# check if performance package installed
perf_installed <- requireNamespace("performance", quietly = TRUE)
## ---- eval = perf_installed---------------------------------------------------
# library(performance)
#
# # the check_outliers function outputs a logical vector which flags specific points as outliers.
# # We need to wrap this to give a single TRUE/FALSE output, where FALSE means it doesn't pass,
# # i.e. there are outliers
# outlier_pass <- function(x){
# # return FALSE if any outliers
# !any(check_outliers(x))
# }
#
# # now call treat(), passing this function
# # we set f_pass_para to NULL to avoid passing default parameters to the new function
# coin <- Treat(coin, dset = "Raw",
# global_specs = list(f_pass = "outlier_pass",
# f_pass_para = NULL)
# )
#
# # see what happened
# coin$Analysis$Treated$Dets_Table |>
# head(10)
## -----------------------------------------------------------------------------
# build example purse
purse <- build_example_purse(up_to = "new_coin", quietly = TRUE)
# apply treatment to all coins in purse (default specs)
purse <- Treat(purse, dset = "Raw")
## -----------------------------------------------------------------------------
# select three indicators
df1 <- ASEM_iData[c("Flights", "Goods", "Services")]
# treat data frame, changing winmax and skew/kurtosis limits
l_treat <- qTreat(df1, winmax = 1, skew_thresh = 1.5, kurt_thresh = 3)
## -----------------------------------------------------------------------------
l_treat$Dets_Table
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