tsdataleaks

In tsdataleaks: Exploit Data Leakages in Time Series Forecasting Competitions

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(tsdataleaks)
library(ggplot2)
library(dplyr)
library(tidyr)
library(viridis)

To demonstrate the package functions, I created a small data set with 4 time series.

set.seed(2020)
a <- rnorm(15)
d <- rnorm(10)
lst <- list(
  a = a,
  b = c(a[10:15]+rep(8,6), rnorm(10), a[1:5], a[1:5]),
  c = c(rnorm(10), a[1:5]),
  d = d,
  e = d)

find_dataleaks: Exploit data leaks

# h - I assume test period length is 5 and took that as wind size, h.
f1 <- find_dataleaks(lstx = lst, h=5, cutoff=1) 
f1

Interpretation: The first element in the list means the last 5 observations of the time series a correlates with time series b observarion from 2 to 6.

viz_dataleaks: Visualise the data leaks

viz_dataleaks(f1)

reason_dataleaks

Display the reasons for data leaks and evaluate usefulness of data leaks towards the winning of the competition

r1 <- reason_dataleaks(lstx = lst, finddataleaksout = f1, h=5)
r1

tsdataleaks documentation built on May 29, 2024, 9:23 a.m.