Matches in SemOpenAlex for { <https://semopenalex.org/work/W2789339966> ?p ?o ?g. }
- W2789339966 endingPage "752" @default.
- W2789339966 startingPage "727" @default.
- W2789339966 abstract "In this paper, we study the family of renewal shot-noise processes. The Feynmann–Kac formula is obtained based on the piecewise deterministic Markov process theory and the martingale methodology. We then derive the Laplace transforms of the conditional moments and asymptotic moments of the processes. In general, by inverting the Laplace transforms, the asymptotic moments and the first conditional moments can be derived explicitly; however, other conditional moments may need to be estimated numerically. As an example, we develop a very efficient and general algorithm of Monte Carlo exact simulation for estimating the second conditional moments. The results can be then easily transformed to the counterparts of discounted aggregate claims for insurance applications, and we apply the first two conditional moments for the actuarial net premium calculation. Similarly, they can also be applied to credit risk and reliability modelling. Numerical examples with four distribution choices for interarrival times are provided to illustrate how the models can be implemented." @default.
- W2789339966 created "2018-03-29" @default.
- W2789339966 creator A5020340282 @default.
- W2789339966 creator A5070431645 @default.
- W2789339966 creator A5072092319 @default.
- W2789339966 date "2018-03-20" @default.
- W2789339966 modified "2023-09-25" @default.
- W2789339966 title "Moments of renewal shot-noise processes and their applications" @default.
- W2789339966 cites W1540131366 @default.
- W2789339966 cites W1895873519 @default.
- W2789339966 cites W1972253250 @default.
- W2789339966 cites W1973795823 @default.
- W2789339966 cites W1977023568 @default.
- W2789339966 cites W1980821331 @default.
- W2789339966 cites W1981137970 @default.
- W2789339966 cites W1985545815 @default.
- W2789339966 cites W1995453571 @default.
- W2789339966 cites W2001244105 @default.
- W2789339966 cites W2005171207 @default.
- W2789339966 cites W2010166971 @default.
- W2789339966 cites W2010463282 @default.
- W2789339966 cites W2013225714 @default.
- W2789339966 cites W2020850534 @default.
- W2789339966 cites W2021672805 @default.
- W2789339966 cites W2025758124 @default.
- W2789339966 cites W2055390972 @default.
- W2789339966 cites W2058770011 @default.
- W2789339966 cites W2060218460 @default.
- W2789339966 cites W2079491906 @default.
- W2789339966 cites W2081420007 @default.
- W2789339966 cites W2083382325 @default.
- W2789339966 cites W2088549373 @default.
- W2789339966 cites W2095330392 @default.
- W2789339966 cites W2101346572 @default.
- W2789339966 cites W2103071636 @default.
- W2789339966 cites W2123681453 @default.
- W2789339966 cites W2143682759 @default.
- W2789339966 cites W2313961709 @default.
- W2789339966 cites W2314900852 @default.
- W2789339966 cites W2963002972 @default.
- W2789339966 cites W3121777840 @default.
- W2789339966 cites W3123321876 @default.
- W2789339966 cites W3123381792 @default.
- W2789339966 cites W3125272213 @default.
- W2789339966 cites W3125837313 @default.
- W2789339966 cites W4206793758 @default.
- W2789339966 cites W4235413109 @default.
- W2789339966 cites W4237187143 @default.
- W2789339966 cites W4244996137 @default.
- W2789339966 cites W4247497491 @default.
- W2789339966 cites W4247619688 @default.
- W2789339966 cites W4254100090 @default.
- W2789339966 cites W4292198165 @default.
- W2789339966 cites W91439453 @default.
- W2789339966 doi "https://doi.org/10.1080/03461238.2018.1452285" @default.
- W2789339966 hasPublicationYear "2018" @default.
- W2789339966 type Work @default.
- W2789339966 sameAs 2789339966 @default.
- W2789339966 citedByCount "6" @default.
- W2789339966 countsByYear W27893399662020 @default.
- W2789339966 countsByYear W27893399662021 @default.
- W2789339966 countsByYear W27893399662022 @default.
- W2789339966 countsByYear W27893399662023 @default.
- W2789339966 crossrefType "journal-article" @default.
- W2789339966 hasAuthorship W2789339966A5020340282 @default.
- W2789339966 hasAuthorship W2789339966A5070431645 @default.
- W2789339966 hasAuthorship W2789339966A5072092319 @default.
- W2789339966 hasBestOaLocation W27893399662 @default.
- W2789339966 hasConcept C105795698 @default.
- W2789339966 hasConcept C121332964 @default.
- W2789339966 hasConcept C126255220 @default.
- W2789339966 hasConcept C134306372 @default.
- W2789339966 hasConcept C149782125 @default.
- W2789339966 hasConcept C159886148 @default.
- W2789339966 hasConcept C162748667 @default.
- W2789339966 hasConcept C164660894 @default.
- W2789339966 hasConcept C179254644 @default.
- W2789339966 hasConcept C185429906 @default.
- W2789339966 hasConcept C186215838 @default.
- W2789339966 hasConcept C2780033567 @default.
- W2789339966 hasConcept C28826006 @default.
- W2789339966 hasConcept C33923547 @default.
- W2789339966 hasConcept C48406656 @default.
- W2789339966 hasConcept C74650414 @default.
- W2789339966 hasConcept C97937538 @default.
- W2789339966 hasConceptScore W2789339966C105795698 @default.
- W2789339966 hasConceptScore W2789339966C121332964 @default.
- W2789339966 hasConceptScore W2789339966C126255220 @default.
- W2789339966 hasConceptScore W2789339966C134306372 @default.
- W2789339966 hasConceptScore W2789339966C149782125 @default.
- W2789339966 hasConceptScore W2789339966C159886148 @default.
- W2789339966 hasConceptScore W2789339966C162748667 @default.
- W2789339966 hasConceptScore W2789339966C164660894 @default.
- W2789339966 hasConceptScore W2789339966C179254644 @default.
- W2789339966 hasConceptScore W2789339966C185429906 @default.
- W2789339966 hasConceptScore W2789339966C186215838 @default.
- W2789339966 hasConceptScore W2789339966C2780033567 @default.
- W2789339966 hasConceptScore W2789339966C28826006 @default.