Bibliographic Details
| Title: |
Robust scale estimation for strongly mixing processes under shifts in the mean. |
| Authors: |
Axt, Ieva1 (AUTHOR), Fried, Roland1 (AUTHOR) fried@statistik.tu-dortmund.de |
| Source: |
Statistics. Aug2026, Vol. 60 Issue 4, p1240-1258. 19p. |
| Subject Terms: |
*Standard deviations, *Outliers (Statistics), *Change-point problems, *Simulation methods & models, *Ergodic theory, *Estimation theory |
| Abstract: |
Knowledge of the variance or standard deviation of a process is crucial in many applications, e.g., for standardization or assessment of uncertainty. Traditional estimators of scale, like the sample variance, exhibit significant bias when faced with outliers or shifts in the mean. In this work, we establish the strong consistency of a blockwise modification of the MAD for strongly mixing processes. A simulation study is conducted to examine the properties of this estimation approach in the possible presence of outliers and level shifts. [ABSTRACT FROM AUTHOR] |
| Database: |
Academic Search Index |