Skip to content

outliers.ts.oga

Efficient Outlier Detection for Large Time Series Databases

v1.1.2 · Jan 30, 2026 · GPL-3

Description

Programs for detecting and cleaning outliers in single time series and in time series from homogeneous and heterogeneous databases using an Orthogonal Greedy Algorithm (OGA) for saturated linear regression models. The programs implement the procedures presented in the paper entitled "Efficient Outlier Detection for Large Time Series Databases" by Pedro Galeano, Daniel Peña and Ruey S. Tsay (2026), working paper, Universidad Carlos III de Madrid. Version 1.1.2 fixes one bug.

Downloads

216

Last 30 days

21210th

614

Last 90 days

2K

Last year

Trend: -16.9% (30d vs prior 30d)

CRAN Check Status

14 OK
Show all 14 flavors
Flavor Status
r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies caret forecast future future.apply gsarima parallelly (>= 1.37.1) robust outliers.ts.oga

Version History

new 1.1.2 Mar 10, 2026
updated 1.1.2 ← 1.1.1 diff Jan 29, 2026
updated 1.1.1 ← 1.0.1 diff Sep 2, 2025
updated 1.0.1 ← 0.0.1 diff Feb 26, 2025
new 0.0.1 May 27, 2024