In sevvandi/composits: Compositional, Multivariate and Univariate Time Series Outlier Ensemble

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

composits

The goal of composits is to find outliers in compositional, multivariate and univariate time series. It is an outlier ensemble method that uses the packages forecast, tsoutliers, anomalize and otsad.

Installation

You can install the released version of composits from CRAN with:

install.packages("composits")

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("sevvandi/composits")

Example

library(composits)
set.seed(100)
n <- 600
x <- sample(1:100, n, replace=TRUE)
x[320] <- 300
x2 <- sample(1:100, n, replace=TRUE)
x3 <- sample(1:100, n, replace=TRUE)
X <- cbind.data.frame(x, x2, x3)
x4 <- sample(1:100, n, replace=TRUE)
X <- cbind.data.frame(x, x2, x3, x4)
out <- mv_tsout_ens(X)
out$all
out$outliers

See our website or our paper [@composits] for more examples.

References

sevvandi/composits documentation built on June 2, 2022, 11:47 p.m.