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On laws exhibiting universal ordering under stochastic restart
- Source :
- Communications in statistics. Theory and methods, vol. 51, no. 5, pp. 1290-1305, 2022.
- Publication Year :
- 2023
- Publisher :
- Taylor & Francis, 2023.
-
Abstract
- For each of (i) arbitrary stochastic reset, (ii) deterministic reset with arbitrary period, (iii) reset at arbitrary constant rate, and then in the sense of either (a) first-order stochastic dominance or (b) expectation (i.e. for each of the six possible combinations of the preceding), those laws of random times are precisely characterized that are rendered no bigger [rendered no smaller; left invariant] by all possible restart laws (within the classes (i), (ii), (iii), as the case may be). Partial results in the same vein for reset with branching are obtained. In particular it is found that deterministic and arbitrary stochastic restart lead to the same characterizations, but this equivalence fails to persist for exponential (constant-rate) reset.
- Subjects :
- Statistics and Probability
zanesljivost
iskanje s ponastavljanjem
0211 other engineering and technologies
FOS: Physical sciences
Stochastic dominance
stochastic restart
Mathematics - Statistics Theory
Statistics Theory (math.ST)
02 engineering and technology
Computer Science::Computational Geometry
01 natural sciences
010104 statistics & probability
reset search
branching
stohastično ponastavljanje
stohastična dominanca prvega reda
FOS: Mathematics
Applied mathematics
first-order stochastic dominance
0101 mathematics
Mathematics
021103 operations research
reliability
Quantitative Biology::Neurons and Cognition
Reset (finance)
Probability (math.PR)
razvejanje
Constant rate
new better than old distributions
Physics - Data Analysis, Statistics and Probability
nove boljše kot stare porazdelitve
Computer Science::Programming Languages
udc:519.213
Data Analysis, Statistics and Probability (physics.data-an)
Mathematics - Probability
Computer Science::Formal Languages and Automata Theory
Subjects
Details
- Language :
- English
- ISSN :
- 03610926
- Database :
- OpenAIRE
- Journal :
- Communications in statistics. Theory and methods, vol. 51, no. 5, pp. 1290-1305, 2022.
- Accession number :
- edsair.doi.dedup.....518899e902368a6817423c97ee85100e