Score matching filters for Gaussian Markov random fields with a linear model of the precision matrix

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F21%3A00551812" target="_blank" >RIV/67985807:_____/21:00551812 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.3934/fods.2021030" target="_blank" >http://dx.doi.org/10.3934/fods.2021030</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3934/fods.2021030" target="_blank" >10.3934/fods.2021030</a>

Result language
angličtina
Original language name
Score matching filters for Gaussian Markov random fields with a linear model of the precision matrix
Original language description
We present an ensemble filtering method based on a linear model for the precision matrix (the inverse of the covariance) with the parameters determined by Score Matching Estimation. The method provides a rigorous covariance regularization when the underlying random field is Gaussian Markov. The parameters are found by solving a system of linear equations. The analysis step uses the inverse formulation of the Kalman update. Several filter versions, differing in the construction of the analysis ensemble, are proposed, as well as a Score matching version of the Extended Kalman Filter.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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