3 citations · 8 across the 8 of their papers we have counts for
6 papers · 1 filter
Efficient Quantile Tracking Using an Oracle
Hugo L. Hammer, Anis Yazidi, Michael A. Riegler +1
For incremental quantile estimators the step size and possibly other tuning parameters must be carefully set. However, little attention has been given on how to set these values in…
Estimating Tukey Depth Using Incremental Quantile Estimators
Hugo Lewi Hammer, Anis Yazidi, Håvard Rue
The concept of depth represents methods to measure how deep an arbitrary point is positioned in a dataset and can be seen as the opposite of outlyingness. It has proved very useful…
Joint Tracking of Multiple Quantiles Through Conditional Quantiles
Hugo Lewi Hammer, Anis Yazidi, Håvard Rue
Estimation of quantiles is one of the most fundamental real-time analysis tasks. Most real-time data streams vary dynamically with time and incremental quantile estimators document…
Quantile Tracking in Dynamically Varying Data Streams Using a Generalized Exponentially Weighted Average of Observations
Hugo Lewi Hammer, Anis Yazidi, Håvard Rue
The Exponentially Weighted Average (EWA) of observations is known to be state-of-art estimator for tracking expectations of dynamically varying data stream distributions. However,…
Parameter Estimation in Abruptly Changing Dynamic Environments
Hugo Lewi Hammer, Anis Yazidi
Many real-life dynamical systems change abruptly followed by almost stationary periods. In this paper, we consider streams of data with such abrupt behavior and investigate the pro…
Estimation of Multiple Quantiles in Dynamically Varying Data Streams
Hugo Lewi Hammer, Anis Yazidi, Håvard Rue
In this paper we consider the problem of estimating quantiles when data are received sequentially (data stream). For real life data streams, the distribution of the data typically…