作者：Chan, NH; Peng, L
作者单位：Chinese University of Hong Kong; University System of Georgia; Georgia Institute of Technology
摘要：The weighted least absolute deviations estimator is studied for an AR(1) process with ARCH(1) errors c, Unlike for the quasi maximum likelihood estimator, the estimator's limiting distribution is shown to be normal even when E(epsilon(4)(t)) = infinity. Furthermore, the estimator can be applied to examine the symmetry of the density of epsilon(t) and to estimate the quantity E(log vertical bar alpha + lambda(1/2)epsilon(t)vertical bar), which are of crucial importance for conducting asymptotic...
作者：Yang, YH
作者单位：University of Minnesota System; University of Minnesota Twin Cities
摘要：A traditional approach to statistical inference is to identify the true or best model first with little or no consideration of the specific goal of inference in the model identification stage. Can the pursuit of the true model also lead to optimal regression estimation? In model selection, it is well known that BIC is consistent in selecting the true model, and AIC is minimax-rate optimal for estimating the regression function. A recent promising direction is adaptive model selection, in which...
