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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.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 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 9, 2026