Show simple item record

dc.contributor.authorThompson, James R.
Atkinson, E. Neely
Brown, Barry
dc.date.accessioned 2018-06-18T17:27:11Z
dc.date.available 2018-06-18T17:27:11Z
dc.date.issued 1986-08
dc.identifier.citation Thompson, James R., Atkinson, E. Neely and Brown, Barry. "SIMEST: An Algorithm for Simulation Based Estimation of Parameters Characterizing a Stochastic Process." (1986) https://hdl.handle.net/1911/101607.
dc.identifier.urihttps://hdl.handle.net/1911/101607
dc.description.abstract The axioms defining stochastic processes are generally simple. However, estimation of the parameters of a process from data is extremely difficult if customary techniques are used. This is due to the complexities involved in obtaining closed forms of likelihoods and evaluating them. The authors develop an estimation technique which selects those parameters which produce simulations that best mimic the data. SIMEST makes stochastic process modelling in oncology (and other fields) an attractive alternative to such currently popular alternatives as ad hoc regression models.
dc.format.extent 52 pp
dc.title SIMEST: An Algorithm for Simulation Based Estimation of Parameters Characterizing a Stochastic Process
dc.type Technical report
dc.date.note August 1986
dc.identifier.digital TR86-20
dc.type.dcmi Text


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record