On the choice and linkage of large scale forecasting models
dc.contributor.author | Chen, Kan | en_US |
dc.date.accessioned | 2006-04-07T16:31:31Z | |
dc.date.available | 2006-04-07T16:31:31Z | |
dc.date.issued | 1976 | en_US |
dc.identifier.citation | Chen, Kan (1976)."On the choice and linkage of large scale forecasting models." Technological Forecasting and Social Change 9(1-2): 27-33. <http://hdl.handle.net/2027.42/21861> | en_US |
dc.identifier.uri | http://www.sciencedirect.com/science/article/B6V71-45K6TJ3-DK/2/5ab04f6be2d7bf3221f719a78870f251 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/21861 | |
dc.description.abstract | Different kinds of large scale forecasting models are compared on the basis of their forecasting time horizons. The choice of model or models should be guided by the decisions to be made. The linkage between models will be facilitated by further developments that will make the models epistemologically compatible. To enhance utilization, the imbedding of forecasting models in some use-oriented framework may be more important than the linkage between models. | en_US |
dc.format.extent | 563444 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Elsevier | en_US |
dc.title | On the choice and linkage of large scale forecasting models | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Engineering (General) | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Electrical and Computer Engineering, University of Michigan, Ann Arbor, Michigan 48104, USA | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/21861/1/0000265.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1016/0040-1625(76)90042-1 | en_US |
dc.identifier.source | Technological Forecasting and Social Change | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.