The bootstrap is a popular and useful tool for estimating the asymptotic variance of complicated estimators. Ironically, the fact that the estimators are complicated can make the standard bootstrap computationally burdensome because it requires repeated re-calculation of the estimator. In this paper, we propose a method which is specific to extremum estimators based on U -statistics. The contri...

The breakdown point behavior of M-estimators in linear models with xed designs, arising from planned experiments or qualitative factors, is characterized. Particularly, this behavior at xed designs is quite diierent from that at designs which can be corrupted by outliers|the situation prevailing in the literature. For xed designs, the breakdown points of robust M-estimators (those with bounded ...

Characterizing the sensitivity to infinitesimally small perturbations in parameters is a powerful tool for the analysis, modeling, and design of chemical reaction networks. Sensitivity analysis of networks modeled using stochastic chemical kinetics, in which a probabilistic description is used to characterize the inherent randomness of the system, is commonly performed using Monte Carlo methods...

The problem of estimating regression coefficients from observations at a finite number of properly designed sampling points is considered when the error process has correlated values and no quadratic mean derivative. Sacks and Ylvisaker (1966, Ann. Math. Statist., 39, 66-89) found an asymptotically optimal design for the best linear unbiased estimator (BLUE). Here, the goal is to find an asympt...

This paper is concerned with nonparametric estimation of the Lévy density of a pure jump Lévy process. The sample path is observed at n discrete instants with fixed sampling interval. We construct a collection of estimators obtained by deconvolution methods and deduced from appropriate estimators of the characteristic function and its first derivative. We obtain a bound for the L-risk, under ge...

The study examined the impact of derivatives usage on performance Shari'ah-compliant firms in Malaysia. employed a Generalised Method-of-Moment estimator (System-GMM) set panel data from 2012 to 2017. A paired sample t-test for mean difference and Wilcoxon Signed-ranks test was performed examine between users non-users derivatives. provided strong evidence significant Moreover, observed better ...

In this paper, the problem of identifying a hidden Markov model (HMM) with general state space, e.g. a partially observed diffusion process, is considered. A particle implementation of the recursive maximum likelihood estimator for a parameter in the transition kernel of the Markov chain is presented. The key assumption is that the derivative of the transition kernel w.r.t. the parameter has a ...

let be a random sample from a normal distribution with unknown mean and known variance the usual estimator of the mean, i.e., sample mean is the maximum likelihood estimator which under squared error loss function is minimax and admissible estimator. in many practical situations, is known in advance to lie in an interval, say for some in this case, the maximum likelihood estimator changes and d...

This paper presents a new methodology for modeling the inductance curves of switched-reluctance machines using cubic splines based on Lagrange form polynomials. The proposed allows estimation instantaneous and derivative in each phase machine. All steps are presented discussed, detailing information necessary its use. results an experimental computational simulation, both as motor generator, es...