title: Stochastical computation methods and experimental designing
metadata.name: dc.contributor.author
metadata.value: Ermakov, Sergei M.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Melas, Vyacheslav B.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2023-05-18T20:13:22Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2023-05-18T20:13:22Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2023-05
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Ermakov S.M., Melas V.B. Stochastical computation methods and experimental designing. Vestnik of Saint Petersburg University. Mathematics. Mechanics. Astronomy, 2023, vol. 10 (68), issue 2, pp. 187–199. https://doi.org/10.21638/spbu01.2023.201 (In Russian)
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/spbu01.2023.201
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/41477
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: This paper contains a brief review of the most important results obtained by the staff of the
  department of statistical modeling. Results include mathematical justification of computer
  simulation of randomness, stochastic methods of solving equations, stochastic optimization,
  study of stochastic stability and parallelism of Monte-Carlo algorithms. In the area
  of experiment planning, special attention is paid to regression experiment under nonlinear
  parameterization. The list of references mainly includes monographs written by members
  of the department. The exceptions are some articles with results not included in them.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Mathematics. Mechanics. Astronomy;Volume 10; Issue 2
metadata.lang: -
metadata.name: dc.subject
metadata.value: stochastic modeling
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: Monte-Carlo method
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: pseudorandom numbers
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: pseudorandom numbers
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: Markov chains
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: stochastic optimization
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: regression experiment
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: optimal experiment design
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: regression models nonlinear in parameters
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: functional approach
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: hyper exponential models
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: fractionally rational models
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: locally optimal experimental designs
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Stochastical computation methods and experimental designing
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 187-199.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/41477/1/187-199.pdf
resources.format: Adobe PDF
resources.size: 340,92 kB