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The Gaussian MLE ve...
The Gaussian MLE versus the Optimally weighted LSE
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- Abdalmoaty, Mohamed, 1986- (author)
- KTH,Reglerteknik,System Identification,Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden
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- Hjalmarsson, Håkan, 1962- (author)
- KTH,Reglerteknik,System Identification,Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden
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- Wahlberg, Bo, 1959- (author)
- KTH,Reglerteknik,System Identification,Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers (IEEE), 2020
- 2020
- English.
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In: IEEE signal processing magazine (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1053-5888 .- 1558-0792. ; 37:6, s. 195-199
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Abstract
Subject headings
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- In this note, we derive and compare the asymptotic covariance matrices of two parametric estimators: the Gaussian Maximum Likelihood Estimator (MLE), and the optimally weighted Least-Squares Estimator (LSE). We assume a general model parameterization where the model's mean and variance are jointly parameterized, and consider Gaussian and non-Gaussian data distributions.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Keyword
- Gaussian MLE
- optimally weighted LSE
- least squares
- optimal weighting
- semi-parametric models
- parameter estimation
- system identification
- Electrical Engineering
- Elektro- och systemteknik
Publication and Content Type
- ref (subject category)
- art (subject category)
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