Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1148791 | Journal of Statistical Planning and Inference | 2006 | 22 Pages |
Abstract
High breakdown-point regression estimators protect against large errors both in explanatory and dependent variables. The least trimmed squares (LTS) estimator is one of frequently used, easily understandable and, from the robustness point of view, thoroughly studied high breakdown-point estimators. In spite of its increasing popularity and a number of applications, very little is known about its asymptotic behaviour in nonlinear, panel-data, and time-series regression after two decades of its existence. In this context, we derive and discuss all important asymptotic properties of LTS, including the asymptotic normality and variance, under mild ββ-mixing conditions.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Pavel Čížek,