Weighted L1-estimates for the First-order Bifurcating Autoregressive Model. Issue 8 (13th September 2016) - Elbayoumi, Tamer M.; Terpstra, Jeff
Abstract : We developed robust estimators that minimize a weighted L 1 norm for the first-order bifurcating autoregressive model. When all of the weights are fixed, our estimate is an L 1 estimate that is robust against outlying points in the response space and more efficient than the least squares estimate for heavy-tailed error distributions. When the weights are random and depend on the points in the factor space, the weighted L 1 estimate is robust against outlying points in the factor space. Simulated and artificial examples are presented. The behavior of the proposed estimate is modeled through a Monte Carlo study.