Linear Inverse Problem with Range Prior on Correlations and Its Variational Bayes Inference

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00474383" target="_blank" >RIV/67985556:_____/17:00474383 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-54084-9_9" target="_blank" >http://dx.doi.org/10.1007/978-3-319-54084-9_9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-54084-9_9" target="_blank" >10.1007/978-3-319-54084-9_9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Linear Inverse Problem with Range Prior on Correlations and Its Variational Bayes Inference

Popis výsledku v původním jazyce

The choice of regularization for an ill-conditioned linear inverse problem has significant impact on the resulting estimates. We consider a linear inverse model with on the solution in the form of zero mean Gaussian prior and with covariance matrix represented in modified Cholesky form. Elements of the covariance are considered as hyper-parameters with truncated Gaussian prior. The truncation points are obtained from expert judgment as range on correlations of selected elements of the solution. This model is motivated by estimation of mixture of radionuclides from gamma dose rate measurements under the prior knowledge on range of their ratios. Since we aim at high dimensional problems, we use the Variational Bayes inference procedure to derive approximate inference of the model. The method is illustrated and compared on a simple example and on more realistic 6 hours long release of mixture of 3 radionuclides.

Název v anglickém jazyce

Linear Inverse Problem with Range Prior on Correlations and Its Variational Bayes Inference

Popis výsledku anglicky

The choice of regularization for an ill-conditioned linear inverse problem has significant impact on the resulting estimates. We consider a linear inverse model with on the solution in the form of zero mean Gaussian prior and with covariance matrix represented in modified Cholesky form. Elements of the covariance are considered as hyper-parameters with truncated Gaussian prior. The truncation points are obtained from expert judgment as range on correlations of selected elements of the solution. This model is motivated by estimation of mixture of radionuclides from gamma dose rate measurements under the prior knowledge on range of their ratios. Since we aim at high dimensional problems, we use the Variational Bayes inference procedure to derive approximate inference of the model. The method is illustrated and compared on a simple example and on more realistic 6 hours long release of mixture of 3 radionuclides.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/7F14287" target="_blank" >7F14287: Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI)</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Bayesian Statistics in Action: BAYSM 2016

ISBN

978-3-319-54084-9

ISSN

2194-1009

e-ISSN

2194-1017

Počet stran výsledku

11

Strana od-do

91-101

Název nakladatele

Springer International Publishing

Místo vydání

Cham

Místo konání akce

Florence

Datum konání akce

19. 6. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000418403500009