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GMM with Many Moment Conditions [PDF]
Econometrica, 2006 This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimators when the number of moment conditions is allowed to increase with the sample size and the moment conditions may be weak. Examples in which these asymptotics are relevant include instrumental variable (IV) estimation with many (possibly weak or ...
Peter C. B. Phillips, Chirok Han
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IEEE Robotics and Automation Letters, 2018
This letter presents a robust Gaussian mixture model registration technique to enable mapping and navigation in dark, complex, unstructured domains such as caves and mines. Subterranean environments are often unmapped and challenged by low-lighting conditions and communication constraints.
Wennie Tabib +2 more
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This letter presents a robust Gaussian mixture model registration technique to enable mapping and navigation in dark, complex, unstructured domains such as caves and mines. Subterranean environments are often unmapped and challenged by low-lighting conditions and communication constraints.
Wennie Tabib +2 more
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SSRN Electronic Journal, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Firpo, Sergio +4 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Firpo, Sergio +4 more
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Implied Probabilities in GMM Estimators
Econometrica, 1993The conventional way to estimate a distribution function is to assume it belongs to a class parameterized by a finite-dimensional vector and then estimate the unknown parameter vector. In many cases, e.g., regression models, part of the assumption is of the form: a given function of the data and of the parameter vector has a zero mean.
Back, Kerry, Brown, David P
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Comparison of GMM and fuzzy-GMM applied to phoneme classification
2009 3rd International Conference on Signals, Circuits and Systems (SCS), 2009The increasing need for more natural human machine interfaces has generated intensive research work directed toward designing and implementing natural speech enabled systems. Because it is very hard to constrain a speaker when expressing a voice-based request, speech recognition systems have to be able to handle out of vocabulary words in the users ...
Kacem Abida, Fakhri Karray, Jiping Sun
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A Computational Implementation of GMM [PDF]
SSRN Electronic Journal, 2014 In this paper we study a statistical method of implementing quasi-Bayes estimators for nonlinear and nonseparable GMM models, that is motivated by the ideas proposed in Chernozhukov and Hong (2003) and Creel and Kristensen (2011) and that combines simulation with nonparametric regression in the computation of GMM models.
Jiti Gao, Han Hong
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GMM-based significance decoding
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013The accuracy of automatic speech recognition systems in noisy and reverberant environments can be improved notably by exploiting the uncertainty of the estimated speech features using so-called uncertainty-of-observation techniques. In this paper, we introduce a new Bayesian decision rule that can serve as a mathematical framework from which both known
Ahmed Hussen Abdelaziz +4 more
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