A Bayesian Approach to Analyzing Uncertainty Among Stochastic Models

78 12 54 2 131 document 54 RR-74-016.pdf application/pdf c841acd77fbe8e649ffc217f1173de95 MD5 289040 2016-01-15 01:40:41 https://pure.iiasa.ac.at/id/eprint/78/1/RR-74-016.pdf 78 1 1 text en public

RR-74-016.pdf

14 31465 1 43197 document 31465 indexcodes.txt text/plain 0d02f6cf06468b0dae59d6625cd54d08 MD5 3228 2016-01-16 00:05:13 https://pure.iiasa.ac.at/id/eprint/78/2/indexcodes.txt 78 2 2 text/plain other Generate index codes conversion from text to indexcodes en public

indexcodes.txt

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/54 31480 2 43212 document 31480 lightbox.jpg image/png 9fdafbe2b5efab78c3dcfaf16200b5f2 MD5 8067 2016-01-16 00:05:46 https://pure.iiasa.ac.at/id/eprint/78/3/lightbox.jpg 78 3 3 image/png other Thumbnails conversion from text to thumbnail_lightbox en public

lightbox.jpg

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/islightboxThumbnailVersionOf https://pure.iiasa.ac.at/id/document/54 31481 2 43213 document 31481 preview.jpg image/png bd86ad47759ff8c5da39b2f6feaf7d2b MD5 3639 2016-01-16 00:05:47 https://pure.iiasa.ac.at/id/eprint/78/4/preview.jpg 78 4 4 image/png other Thumbnails conversion from text to thumbnail_preview en public

preview.jpg

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/ispreviewThumbnailVersionOf https://pure.iiasa.ac.at/id/document/54 31482 2 43214 document 31482 medium.jpg image/png e41ac0f5b49dacea942918dcb8e6f057 MD5 1632 2016-01-16 00:05:48 https://pure.iiasa.ac.at/id/eprint/78/5/medium.jpg 78 5 5 image/png other Thumbnails conversion from text to thumbnail_medium en public

medium.jpg

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/ismediumThumbnailVersionOf https://pure.iiasa.ac.at/id/document/54 31483 2 43215 document 31483 small.jpg image/png f98893f5b9b93302e0b65b49d90c5a50 MD5 910 2016-01-16 00:05:49 https://pure.iiasa.ac.at/id/eprint/78/6/small.jpg 78 6 6 image/png other Thumbnails conversion from text to thumbnail_small en public

small.jpg

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/issmallThumbnailVersionOf https://pure.iiasa.ac.at/id/document/54 66528 2 185097 document 66528 RR-74-016.pdf application/pdf 90763dcfd0a08d41b0766bf5548e3a24 MD5 503405 2016-07-21 19:27:14 https://pure.iiasa.ac.at/id/eprint/78/7/RR-74-016.pdf 78 7 7 application/pdf other Coversheet Pages conversion from text to application/pdf en public

RR-74-016.pdf

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/54 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/54 archive 351 disk0/00/00/00/78 2016-01-15 01:40:41 2021-08-27 17:07:23 2016-01-15 01:40:41 monograph show 2 Wood E.F. AL0423 A Bayesian Approach to Analyzing Uncertainty Among Stochastic Models pub iis_met iis_mod prog_sds prog_ren The statistical uncertainty, resulting from the lack of knowledge of which modeling represents a given stochastic process, is analyzed. This analysis of model uncertainty leads to a composite Bayesian distribution. The composite Bayesian distribution is a linear model of the individual Bayesian probability distributions of the individual models, weighted by the posterior probability that a particular model is the true model. The composite Bayesian probability model accounts for all sources of statistical uncertainty -- both parameter uncertainty and model uncertainty. This model is the one that should be used in applied problems of decision analysis, for it best represents the knowledge -- or lack of it -- to the decision maker about future events of the process. 1974-09 published RR-74-016 RR-74-016 10 2525 public research_report IIASA, Laxenburg, Austria 19 TRUE FALSE info:eu-repo/semantics/book