1996
DOI: 10.1016/0895-7177(96)00038-6
|View full text |Cite
|
Sign up to set email alerts
|

Smoothness and dimension reduction in Quasi-Monte Carlo methods

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

2
125
0
1

Year Published

2004
2004
2021
2021

Publication Types

Select...
5
2
1

Relationship

0
8

Authors

Journals

citations
Cited by 149 publications
(130 citation statements)
references
References 14 publications
2
125
0
1
Order By: Relevance
“…The convergence rate of QMC depends on the smoothness of the summand and it may deteriorate because of the lack of regularity in v k ω j (x k , φ, t). By introducing a linear approximation of v k close to the switch from 1 to 0, better convergence is achieved in [2,25]. The convergence of the MC and QMC methods are compared using Faure sequences [6] for QMC in a numerical example in Sect.…”
Section: Approximation Of the Summationmentioning
confidence: 99%
See 2 more Smart Citations
“…The convergence rate of QMC depends on the smoothness of the summand and it may deteriorate because of the lack of regularity in v k ω j (x k , φ, t). By introducing a linear approximation of v k close to the switch from 1 to 0, better convergence is achieved in [2,25]. The convergence of the MC and QMC methods are compared using Faure sequences [6] for QMC in a numerical example in Sect.…”
Section: Approximation Of the Summationmentioning
confidence: 99%
“…The acceptance-rejection method (A-R) [2,12] and a smoothing alternative [2,25] are tested. The discontinuity in the A-R method is replaced by a linear function between 0 and 1 in [25]. One important consideration is the fact that when for example the A-R method is used to generate numbers from the distribution, fewer evaluation points will be accepted and used than in e.g.…”
Section: Metabolites Controled By Enzymesmentioning
confidence: 99%
See 1 more Smart Citation
“…The effectiveness of quasi-Monte Carlo for path integrals will be regained using an alternative representation of the random walk, the Brownian Bridge Discretization, which was first introduced as a quasi-Monte Carlo technique by [25]. This representation relies on the following Brownian bridge formula [15] for b(t + ∆t 1 ) knowing b(t) and b(T = t + ∆t 1 + ∆t 2 ):…”
Section: 2mentioning
confidence: 99%
“…The authors have combined this approach with the so-called bridge sampling (see Moskowitz and Caflisch 1996) and have developed a method for sampling from the gamma process. It has been applied by Avramidis et al (2003) to the gamma process used to randomize the time in the Brownian motion representation of the VG process, a method, named Brownian Gamma Bridge Sampling (BGBS).…”
Section: Introductionmentioning
confidence: 99%