FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3046770151> ?p ?o ?g. }

• W3046770151 endingPage "559" @default.
• W3046770151 startingPage "543" @default.
• W3046770151 abstract "A full Bayesian statistical treatment of complex pharmacokinetic or pharmacodynamic models, in particular in a population context, gives access to powerful inference, including on model structure. Markov Chain Monte Carlo (MCMC) samplers are typically used to estimate the joint posterior parameter distribution of interest. Among MCMC samplers, the simulated tempering algorithm (TMCMC) has a number of advantages: it can sample from sharp multi-modal posteriors; it provides insight into identifiability issues useful for model simplification; it can be used to compute accurate Bayes factors for model choice; the simulated Markov chains mix quickly and have assured convergence in certain conditions. The main challenge when implementing this approach is to find an adequate scale of auxiliary inverse temperatures (perks) and associated scaling constants. We solved that problem by adaptive stochastic optimization and describe our implementation of TMCMC sampling in the GNU MCSim software. Once a grid of perks is obtained, it is easy to perform posterior-tempered MCMC sampling or likelihood-tempered MCMC (thermodynamic integration, which bridges the joint prior and the posterior parameter distributions, with assured convergence of a single sampling chain). We compare TMCMC to other samplers and demonstrate its efficient sampling of multi-modal posteriors and calculation of Bayes factors in two stylized case-studies and two realistic population pharmacokinetic inference problems, one of them involving a large PBPK model." @default.
• W3046770151 created "2020-08-07" @default.
• W3046770151 creator A5003171780 @default.
• W3046770151 creator A5005661859 @default.
• W3046770151 creator A5040450111 @default.
• W3046770151 creator A5054433786 @default.
• W3046770151 creator A5080621867 @default.
• W3046770151 date "2020-07-31" @default.
• W3046770151 modified "2023-09-27" @default.
• W3046770151 title "Well-tempered MCMC simulations for population pharmacokinetic models" @default.
• W3046770151 cites W1536497620 @default.
• W3046770151 cites W1545319692 @default.
• W3046770151 cites W1608678137 @default.
• W3046770151 cites W1641947403 @default.
• W3046770151 cites W1941028167 @default.
• W3046770151 cites W1983628095 @default.
• W3046770151 cites W1994616650 @default.
• W3046770151 cites W2011771713 @default.
• W3046770151 cites W2012040766 @default.
• W3046770151 cites W2026627938 @default.
• W3046770151 cites W2030911724 @default.
• W3046770151 cites W2039716779 @default.
• W3046770151 cites W2041215343 @default.
• W3046770151 cites W2043432627 @default.
• W3046770151 cites W2046443205 @default.
• W3046770151 cites W2071668645 @default.
• W3046770151 cites W2073400184 @default.
• W3046770151 cites W2078718575 @default.
• W3046770151 cites W2092872761 @default.
• W3046770151 cites W2114449404 @default.
• W3046770151 cites W2114632070 @default.
• W3046770151 cites W2128981260 @default.
• W3046770151 cites W2148534890 @default.
• W3046770151 cites W2149426275 @default.
• W3046770151 cites W2150821867 @default.
• W3046770151 cites W2155812848 @default.
• W3046770151 cites W2297521569 @default.
• W3046770151 cites W2398325927 @default.
• W3046770151 cites W2625449182 @default.
• W3046770151 cites W2804035554 @default.
• W3046770151 cites W2904923971 @default.
• W3046770151 cites W2928418041 @default.
• W3046770151 cites W2955151712 @default.
• W3046770151 cites W2964191999 @default.
• W3046770151 cites W3099713778 @default.
• W3046770151 cites W3103263318 @default.
• W3046770151 cites W4232632925 @default.
• W3046770151 doi "https://doi.org/10.1007/s10928-020-09705-0" @default.
• W3046770151 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8082542" @default.
• W3046770151 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32737765" @default.
• W3046770151 hasPublicationYear "2020" @default.
• W3046770151 type Work @default.
• W3046770151 sameAs 3046770151 @default.
• W3046770151 citedByCount "7" @default.
• W3046770151 countsByYear W30467701512021 @default.
• W3046770151 countsByYear W30467701512022 @default.
• W3046770151 countsByYear W30467701512023 @default.
• W3046770151 crossrefType "journal-article" @default.
• W3046770151 hasAuthorship W3046770151A5003171780 @default.
• W3046770151 hasAuthorship W3046770151A5005661859 @default.
• W3046770151 hasAuthorship W3046770151A5040450111 @default.
• W3046770151 hasAuthorship W3046770151A5054433786 @default.
• W3046770151 hasAuthorship W3046770151A5080621867 @default.
• W3046770151 hasBestOaLocation W30467701512 @default.
• W3046770151 hasConcept C105795698 @default.
• W3046770151 hasConcept C106131492 @default.
• W3046770151 hasConcept C107673813 @default.
• W3046770151 hasConcept C111350023 @default.
• W3046770151 hasConcept C11413529 @default.
• W3046770151 hasConcept C119857082 @default.
• W3046770151 hasConcept C122770356 @default.
• W3046770151 hasConcept C126255220 @default.
• W3046770151 hasConcept C140779682 @default.
• W3046770151 hasConcept C144024400 @default.
• W3046770151 hasConcept C149923435 @default.
• W3046770151 hasConcept C154945302 @default.
• W3046770151 hasConcept C160234255 @default.
• W3046770151 hasConcept C177769412 @default.
• W3046770151 hasConcept C19499675 @default.
• W3046770151 hasConcept C207201462 @default.
• W3046770151 hasConcept C2908647359 @default.
• W3046770151 hasConcept C31972630 @default.
• W3046770151 hasConcept C33923547 @default.
• W3046770151 hasConcept C41008148 @default.
• W3046770151 hasConcept C52740198 @default.
• W3046770151 hasConcept C57830394 @default.
• W3046770151 hasConceptScore W3046770151C105795698 @default.
• W3046770151 hasConceptScore W3046770151C106131492 @default.
• W3046770151 hasConceptScore W3046770151C107673813 @default.
• W3046770151 hasConceptScore W3046770151C111350023 @default.
• W3046770151 hasConceptScore W3046770151C11413529 @default.
• W3046770151 hasConceptScore W3046770151C119857082 @default.
• W3046770151 hasConceptScore W3046770151C122770356 @default.
• W3046770151 hasConceptScore W3046770151C126255220 @default.
• W3046770151 hasConceptScore W3046770151C140779682 @default.
• W3046770151 hasConceptScore W3046770151C144024400 @default.
• W3046770151 hasConceptScore W3046770151C149923435 @default.
• W3046770151 hasConceptScore W3046770151C154945302 @default.

• next