99 citations · 312 across the 30 of their papers we have counts for
9 papers · 1 filter
When lookout sees crackle: Anomaly detection via kernel density estimation
Rob J Hyndman, Sevvandi Kandanaarachchi, Katharine Turner
We present an updated version of lookout -- an algorithm for detecting anomalies using kernel density estimates with bandwidth based on Rips death diameters -- with theoretical gua…
Anomaly detection using surprisals
Rob J Hyndman, David T. Frazier
Anomaly detection methods are widely used but often rely on ad hoc rules or strong assumptions, and they often focus on tail events, missing ``inlier'' anomalies that occur in low-…
Online conformal inference for multi-step time series forecasting
Xiaoqian Wang, Rob J Hyndman
We study the construction of distribution-free prediction intervals for multi-step time series forecasting. In this setting, forecast errors at different horizons are serially depe…
Forecast Linear Augmented Projection (FLAP): A free lunch to reduce forecast error variance
Yangzhuoran Fin Yang, George Athanasopoulos, Rob J. Hyndman +1
A novel forecast linear augmented projection (FLAP) method is introduced, which reduces the forecast error variance of any unbiased multivariate forecast without introducing bias.…
Conditional normalization in time series analysis
Puwasala Gamakumara, Edgar Santos-Fernandez, Priyanga Dilini Talagala +3
Time series often reflect variation associated with other related variables. Controlling for the effect of these variables is useful when modeling or analysing the time series. We…
Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues
Daniele Girolimetto, George Athanasopoulos, Tommaso Di Fonzo +1
Forecast reconciliation is a post-forecasting process that involves transforming a set of incoherent forecasts into coherent forecasts which satisfy a given set of linear constrain…
Forecast combinations: an over 50-year review
Xiaoqian Wang, Rob J Hyndman, Feng Li +1
Forecast combinations have flourished remarkably in the forecasting community and, in recent years, have become part of the mainstream of forecasting research and activities. Combi…
Modern strategies for time series regression
Stephanie Clark, Rob J Hyndman, Dan Pagendam +1
This paper discusses several modern approaches to regression analysis involving time series data where some of the predictor variables are also indexed by time. We discuss classica…
STR: Seasonal-Trend Decomposition Using Regression
Alexander Dokumentov, Rob J. Hyndman
We propose a new method for decomposing seasonal data: STR (a Seasonal-Trend decomposition using Regression). Unlike other decomposition methods, STR allows for multiple seasonal a…