Title
True ML Estimator for the Location Parameter of the Generalized Gaussian Distribution with p = 4
Abstract
Estimation of the location parameter of the generalized Gaussian distribution with shape parameter p=4 is studied and an explicit solution for the maximum likelihood estimator is derived. The Cramér Rao lower bound is derived and the mean square error of the new estimator is compared to it. The new maximum likelihood estimator attains the Cramér Rao lower bound for a moderate number of samples. Simulation results show the explicit maximum likelihood estimator has superior performance compared to the mean estimator and slightly better performance than the moment/Newton-step estimator. The new maximum likelihood estimator has similar computational complexity to the moment/Newton-step estimator.
Year
DOI
Venue
2013
10.1109/LCOMM.2012.12.121706
Communications Letters, IEEE
Keywords
Field
DocType
Gaussian distribution,Newton method,computational complexity,maximum likelihood estimation,mean square error methods,method of moments,parameter estimation,signal processing,Cramér Rao lower bound,computational complexity,generalized Gaussian distribution,location parameter estimation,maximum likelihood estimator,mean square error,moment-Newton-step estimator,Generalized Gaussian distribution (GGD),location parameter,maximum likelihood (ML) estimator
Efficient estimator,Minimum-variance unbiased estimator,Bias of an estimator,Estimation theory,Trimmed estimator,Statistics,Bayes estimator,Mathematics,Consistent estimator,Estimator
Journal
Volume
Issue
ISSN
17
1
1089-7798
Citations 
PageRank 
References 
2
0.36
5
Authors
2
Name
Order
Citations
PageRank
Norman C. Beaulieu12372285.49
Qintian Guo240.81