Updating Probabilities with Data and Moments Export

@misc{citeulike:1570907, abstract = {We use the method of Maximum (relative) Entropy to process information in the form of observed data and moment constraints. The generic "canonical" form of the posterior distribution for the problem of simultaneous updating with data and moments is obtained. We discuss the general problem of non-commuting constraints, when they should be processed sequentially and when simultaneously. As an illustration, the multinomial example of die tosses is solved in detail for two superficially similar but actually very different problems.}, archivePrefix = {arXiv}, author = {Giffin, Adom and Caticha, Ariel}, citeulike-article-id = {1570907}, citeulike-linkout-0 = {http://arxiv.org/abs/0708.1593}, citeulike-linkout-1 = {http://arxiv.org/pdf/0708.1593}, citeulike-linkout-2 = {http://dx.doi.org/10.1063/1.2821302}, citeulike-linkout-3 = {http://adsabs.harvard.edu/cgi-bin/nph-bib_query?bibcode=2007AIPC..954...74G}, day = {13}, doi = {10.1063/1.2821302}, eprint = {0708.1593}, keywords = {stats}, month = {Aug}, posted-at = {2007-08-16 23:00:40}, priority = {2}, title = {Updating Probabilities with Data and Moments}, url = {http://dx.doi.org/10.1063/1.2821302}, year = {2007} }

TY - ELEC ID - citeulike:1570907 L3 - citeulike-article-id:1570907 N2 - We use the method of Maximum (relative) Entropy to process information in the form of observed data and moment constraints. The generic "canonical" form of the posterior distribution for the problem of simultaneous updating with data and moments is obtained. We discuss the general problem of non-commuting constraints, when they should be processed sequentially and when simultaneously. As an illustration, the multinomial example of die tosses is solved in detail for two superficially similar but actually very different problems. TI - Updating Probabilities with Data and Moments KW - stats AU - Giffin, Adom AU - Caticha, Ariel PY - 2007/Aug/13/ UR - http://dx.doi.org/10.1063/1.2821302 ER -