Compartmental systems and computation their stationary probability vectors
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F12%3A00196695" target="_blank" >RIV/68407700:21110/12:00196695 - isvavai.cz</a>
Výsledek na webu
<a href="http://siamla2012.webs.upv.es/" target="_blank" >http://siamla2012.webs.upv.es/</a>
DOI - Digital Object Identifier
—
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Compartmental systems and computation their stationary probability vectors
Popis výsledku v původním jazyce
To compute stationary probability vectors of Markov chains whose transition matrices are cyclic of index p may be a difficult task if p becomes large. A class of iterative aggregation/disaggregation methods (IAD) is proposed to overcome the difficulty. It is shown that the rate of convergence of the proposed IAD processes is governed by the maximal modulus of the eigenvalues laying out of the peripheral spectrum of the smoothing matrix. The examined generators of Markov chains come from compartmental systems and cause that the transition matrices under consideration may depend upon the appropriate stationary probability vectors. The nonlinearity represents further difficulties in computation.
Název v anglickém jazyce
Compartmental systems and computation their stationary probability vectors
Popis výsledku anglicky
To compute stationary probability vectors of Markov chains whose transition matrices are cyclic of index p may be a difficult task if p becomes large. A class of iterative aggregation/disaggregation methods (IAD) is proposed to overcome the difficulty. It is shown that the rate of convergence of the proposed IAD processes is governed by the maximal modulus of the eigenvalues laying out of the peripheral spectrum of the smoothing matrix. The examined generators of Markov chains come from compartmental systems and cause that the transition matrices under consideration may depend upon the appropriate stationary probability vectors. The nonlinearity represents further difficulties in computation.
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
BA - Obecná matematika
OECD FORD obor
—
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2012
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů