Asymptotically efficient estimation of spectral moments

Asymptotically efficient estimation of spectral moments

This paper studies parametric estimation of spectral moments of a zero-mean complex Gaussian stationary process immersed in independent Gaussian noise. With the merit of the maximum-likelihood (ML) approach as motivation, this work exploits a Whittle’s type objective function able to capture the relevant features of the log-likelihood function, while being much more manageable. The resulting es...

Asymptotically Efficient Estimation of Spectral Moments

Abstmet-This correspondence studies parametric estimatioll of spectral moments of a zero-mean complex Gaussian stationary pmcess immersed in independent Gaussian noise. With the merit of the maximum-likelihood @lL) approach as motivation, this work exploits a Whittle's type objective function that is able to capture the relevant feabues of the log-likelihmdfunction while b e i i much more manag...

Linear Parameter Estimation : Asymptotically Efficient Adaptive Strategies

This paper considers the problem of distributed adaptive linear parameter estimation in multiagent inference networks. Local sensing model information is only partially available at the agents, and interagent communication is assumed to be unpredictable. The paper develops a generic mixed time-scale stochastic procedure consisting of simultaneous distributed learning and estimation, in which th...

Asymptotically Efficient Estimation of the Derivative of the Invariant Density

Asymptotically Efficient Estimation of Linear Functionals in Inverse Regression Models

In this paper we will discuss a procedure to improve the usual estimator of a linear functional of the unknown regression function in inverse nonparametric regression models. In Klaassen et al. (2001) it has been proved that this traditional estimator is not asymptotically efficient (in the sense of the Hájek Le Cam convolution theorem) except, possibly, when the error distribution is normal. S...