We propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error … simulated data. -- Adaptive Estimation; Asymptotic Expansions ; Efficiency ; Kernel ; Local Likelihood Estimation …

density estimation ; nonparametric least squares ; bootstrap inference ; monotonicity ; convexity … the residuals. Static and dynamic properties can be tested using both asymptotic and bootstrap methods. Our monte carlo … simulations suggest that bootstrap confidence intervals are far superior to aymptotic ones particularly when estimating …

and the "moment-oriented" bootstrap method of Bunke which is a wild bootstrap based on smoothed local estimators of higher … order error moments. We show that our bootstrap consistently estimates the distribution of mh(x0) - m(xo). In the present …

The paper is concerned with the estimation of the long memory parameter in a conditionally heteroskedastic model … models ; semiparametric estimation ; modified R/S ; KPSS and V/S statistics ; periodogram …

paper extends this approach to the simultaneous estimation of both the function and its derivatives by combining the … integration procedure with a local polynomial approach. Finally the merits of this procedure with respect to the estimation of a … ; Additive Models ; Derivative Estimation ; Production Function …

asymptotically for the bootstrap to be valid. However, certain model-based bootstrap methods remain valid for some interesting … bootstrap schemes remain valid for supremum-type functionals as long as they mimic the corresponding finite-dimensional joint … distributions consistently. As an example, we investigate a finite order Markov chain bootstrap in the context of a general …

A bootstrap methodology for the periodogram of a stationary process is proposed which is based on a combination of a … time domain parametric and a frequency domain nonparametric bootstrap. The parametric fit is used to generate periodogram … theory developed shows validity of the proposed bootstrap procedure for a large class of periodogram statistics. For …