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Добірка наукової літератури з теми "Optimal stopping rules"

Автор: Grafiati
Опубліковано: 10 грудня 2022
Оновлено: 28 січня 2023

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Статті в журналах з теми "Optimal stopping rules"

1

Assaf, David, and Ester Samuel-Cahn. "Optimal multivariate stopping rules." Journal of Applied Probability 35, no. 3 (September 1998): 693–706. http://dx.doi.org/10.1239/jap/1032265217.

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Анотація:
For fixed i let X(i) = (X1(i), …, Xd(i)) be a d-dimensional random vector with some known joint distribution. Here i should be considered a time variable. Let X(i), i = 1, …, n be a sequence of n independent vectors, where n is the total horizon. In many examples Xj(i) can be thought of as the return to partner j, when there are d ≥ 2 partners, and one stops with the ith observation. If the jth partner alone could decide on a (random) stopping rule t, his goal would be to maximize EXj(t) over all possible stopping rules t ≤ n. In the present ‘multivariate’ setup the d partners must however cooperate and stop at the same stopping time t, so as to maximize some agreed function h(∙) of the individual expected returns. The goal is thus to find a stopping rule t* for which h(EX1 (t), …, EXd(t)) = h (EX(t)) is maximized. For continuous and monotone h we describe the class of optimal stopping rules t*. With some additional symmetry assumptions we show that the optimal rule is one which (also) maximizes EZt where Zi = ∑dj=1Xj(i), and hence has a particularly simple structure. Examples are included, and the results are extended both to the infinite horizon case and to the case when X(1), …, X(n) are dependent. Asymptotic comparisons between the present problem of finding suph(EX(t)) and the ‘classical’ problem of finding supEh(X(t)) are given. Comparisons between the optimal return to the statistician and to a ‘prophet’ are also included. In the present context a ‘prophet’ is someone who can base his (random) choice g on the full sequence X(1), …, X(n), with corresponding return suph(EX(g)).
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2

Assaf, David, and Ester Samuel-Cahn. "Optimal multivariate stopping rules." Journal of Applied Probability 35, no. 03 (September 1998): 693–706. http://dx.doi.org/10.1017/s002190020001634x.

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For fixediletX(i) = (X1(i), …,Xd(i)) be ad-dimensional random vector with some known joint distribution. Hereishould be considered a time variable. LetX(i),i= 1, …,nbe a sequence ofnindependent vectors, wherenis the total horizon. In many examplesXj(i) can be thought of as the return to partnerj, when there ared≥ 2 partners, and one stops with theith observation. If thejth partner alone could decide on a (random) stopping rulet, his goal would be to maximizeEXj(t) over all possible stopping rulest≤n. In the present ‘multivariate’ setup thedpartners must however cooperate and stop at thesamestopping timet, so as to maximize some agreed functionh(∙) of the individual expected returns. The goal is thus to find a stopping rulet*for whichh(EX1(t), …,EXd(t)) =h(EX(t)) is maximized. For continuous and monotonehwe describe the class of optimal stopping rulest*. With some additional symmetry assumptions we show that the optimal rule is one which (also) maximizesEZtwhereZi= ∑dj=1Xj(i), and hence has a particularly simple structure. Examples are included, and the results are extended both to the infinite horizon case and to the case whenX(1), …,X(n) are dependent. Asymptotic comparisons between the present problem of finding suph(EX(t)) and the ‘classical’ problem of finding supEh(X(t)) are given. Comparisons between the optimal return to the statistician and to a ‘prophet’ are also included. In the present context a ‘prophet’ is someone who can base his (random) choicegon the full sequenceX(1), …,X(n), with corresponding return suph(EX(g)).
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3

Karni, Edi, and Zvi Safra. "Behaviorally consistent optimal stopping rules." Journal of Economic Theory 51, no. 2 (August 1990): 391–402. http://dx.doi.org/10.1016/0022-0531(90)90024-e.

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4

Ferguson, T. S., and J. P. Hardwick. "Stopping rules for proofreading." Journal of Applied Probability 26, no. 02 (June 1989): 304–13. http://dx.doi.org/10.1017/s0021900200027303.

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Анотація:
A manuscript with an unknown random numberMof misprints is subjected to a series of proofreadings in an effort to detect and correct the misprints. On thenthproofreading, each remaining misprint is detected independently with probabilitypn– 1. Each proofreading costs an amountCP> 0, and if one stops afternproofreadings, each misprint overlooked costs an amountcn> 0. Two models are treated based on the distribution ofM.In the Poisson model, the optimal stopping rule is seen to be a fixed sample size rule. In the binomial model, the myopic rule is optimal in many important cases. A generalization is made to problems in which individual misprints may have distinct probabilities of detection and distinct overlook costs.
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5

Ferguson, T. S., and J. P. Hardwick. "Stopping rules for proofreading." Journal of Applied Probability 26, no. 2 (June 1989): 304–13. http://dx.doi.org/10.2307/3214037.

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Анотація:
A manuscript with an unknown random number M of misprints is subjected to a series of proofreadings in an effort to detect and correct the misprints. On the nthproofreading, each remaining misprint is detected independently with probability pn– 1. Each proofreading costs an amount CP > 0, and if one stops after n proofreadings, each misprint overlooked costs an amount cn > 0. Two models are treated based on the distribution of M. In the Poisson model, the optimal stopping rule is seen to be a fixed sample size rule. In the binomial model, the myopic rule is optimal in many important cases. A generalization is made to problems in which individual misprints may have distinct probabilities of detection and distinct overlook costs.
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6

Ankirchner, Stefan, and Maike Klein. "Bayesian sequential testing with expectation constraints." ESAIM: Control, Optimisation and Calculus of Variations 26 (2020): 51. http://dx.doi.org/10.1051/cocv/2019045.

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We study a stopping problem arising from a sequential testing of two simple hypotheses H0 and H1 on the drift rate of a Brownian motion. We impose an expectation constraint on the stopping rules allowed and show that an optimal stopping rule satisfying the constraint can be found among the rules of the following type: stop if the posterior probability for H1 attains a given lower or upper barrier; or stop if the posterior probability comes back to a fixed intermediate point after a sufficiently large excursion. Stopping at the intermediate point means that the testing is abandoned without accepting H0 or H1. In contrast to the unconstrained case, optimal stopping rules, in general, cannot be found among interval exit times. Thus, optimal stopping rules in the constrained case qualitatively differ from optimal rules in the unconstrained case.
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7

Chow, Chung-Wen, and Zvi Schechner. "On stopping rules in proofreading." Journal of Applied Probability 22, no. 4 (December 1985): 971–77. http://dx.doi.org/10.2307/3213967.

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8

Chow, Chung-Wen, and Zvi Schechner. "On stopping rules in proofreading." Journal of Applied Probability 22, no. 04 (December 1985): 971–77. http://dx.doi.org/10.1017/s002190020010823x.

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9

Allaart, Pieter, and Michael Monticino. "Optimal stopping rules for directionally reinforced processes." Advances in Applied Probability 33, no. 2 (June 2001): 483–504. http://dx.doi.org/10.1017/s0001867800010909.

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This paper analyzes optimal single and multiple stopping rules for a class of correlated random walks that provides an elementary model for processes exhibiting momentum or directional reinforcement behavior. Explicit descriptions of optimal stopping rules are given in several interesting special cases with and without transaction costs. Numerical examples are presented comparing optimal strategies to simpler buy and hold strategies.
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10

Allaart, Pieter, and Michael Monticino. "Optimal stopping rules for directionally reinforced processes." Advances in Applied Probability 33, no. 2 (2001): 483–504. http://dx.doi.org/10.1239/aap/999188325.

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Дисертації з теми "Optimal stopping rules"

1

Benkherouf, Lakdere. "Optimal stopping rules in oil exploration." Thesis, Imperial College London, 1988. http://hdl.handle.net/10044/1/46958.

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2

Yu, Shiau-Ping, and 余曉萍. "Development of Optimal Stopping Rules for Sequential Sampling Plan." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/74935312944624766199.

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Анотація:
碩士
國立成功大學
統計學系碩博士班
95
During the in-coming and/or outgoing inspection of the industrial products, the decision of accepting or rejecting a lot is made according to the inspection/testing results for the key characteristics of sample units. Additional costs including labor and material costs as well as the loss of mis-judgement usually occur when applying Wald's sequential sampling plan to the destructive testing. Normally, previous stopping rules for Wald's sequential sampling plan are empirically determined based on rules of thumb. Practical and unable to decide whether the sample number for terminating inspection/testing is economical or not . In order to effectively reduce the average sample number of sequential sampling plan, the upper limit of the sample number is specified first, then the optimal stopping rules is determined based on this specified sample number . Finally, a total cost function is established to assess the total loss of the proposed sequential sampling plan . The results show that the optimal stopping rule for our proposed sequential sampling plan can effectively reduce the average sample number and thus achieve a minimum total loss under the reasonable type Ι and Ⅱ errors.
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3

Tai, Chien-Yin, and 戴劍英. "Approximation to Optimal Stopping Rules for Poisson Random Variables." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/13199778980789864589.

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4

Chiang, Hui-Chuan, and 姜惠娟. "Optimal Stopping and Adaptive Rules for Imperfect Debugging with Unequal Failure Rates." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/06645880387517052729.

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5

Win-Chou, Sir, and 周嗣文. "SELECTING THE STOCK ISSUING MEANS USING OPTIMAL STOPPING RULE." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/68219092604011920715.

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6

Ciou, Yi-Hao, and 邱奕豪. "Optimal Look-ahead Stopping Rule and Its Application to American Option." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/95081942287889903528.

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Анотація:
碩士
國立彰化師範大學
數學系所
99
A stopping rule is a nonnegative integer-valued random variable and an optimal stopping rule is a stopping rule which maximizes expectation of the underlying process. Backward induction (Chow, Robbins and Siegmund, 1971), or dubbed as the Snell envelope, provides itself as a rule to find the optimal time to stop the underlying stochastic sequence. In this thesis, we consider a more general class of stopping rules called "k-step look ahead stopping rule" and study their fundamental properties. Moreover, similar to Bensoussan (1984) and Karatzas (1988), we extend the pricing strategy of American options to the class comprising k-step look ahead stopping rules.
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Книги з теми "Optimal stopping rules"

1

Shiri︠a︡ev, Alʹbert Nikolaevich. Optimal stopping rules. Berlin: Springer, 2008.

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2

Srivastava, M. S. Optimal bayes stopping rules for detecting the change point in a bernoulli process. Toronto: University of Toronto, Dept. of Statistics, 1989.

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3

Shiryaev, Albert N. Optimal Stopping Rules. Springer, 2008.

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4

Optimal Stopping Rules. Springer London, Limited, 2007.

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Частини книг з теми "Optimal stopping rules"

1

Shiryaev, Albert N. "Optimal Stopping Rules." In International Encyclopedia of Statistical Science, 1032–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_433.

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2

Chow, Y. S., and Herbert Robbins. "On Optimal Stopping Rules." In Herbert Robbins Selected Papers, 425–41. New York, NY: Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4612-5110-1_39.

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3

Bhattacharya, Rabi, and Edward C. Waymire. "Special Topic: Optimal Stopping Rules." In Graduate Texts in Mathematics, 291–303. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78939-8_24.

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4

Domansky, Victor. "Dynkin’s Games with Randomized Optimal Stopping Rules." In Annals of the International Society of Dynamic Games, 247–62. Boston, MA: Birkhäuser Boston, 2005. http://dx.doi.org/10.1007/0-8176-4429-6_14.

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5

Shiryaev, Albert N. "Optimal Stopping Rules. General Theory for the Continuous-Time Case." In Stochastic Disorder Problems, 93–137. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-01526-8_5.

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6

Barón, Michael I. "Bayes and asymptotically pointwise optimal stopping rules for the detection of influenza epidemics." In Case Studies in Bayesian Statistics, 153–63. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4612-2078-7_5.

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Shiryaev, Albert N. "Optimal Stopping Rules. General Theory for the Discrete-Time Case in the Markov Representation." In Stochastic Disorder Problems, 75–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-01526-8_4.

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8

Polushina, T. V. "Estimating Optimal Stopping Rules in the Multiple Best Choice Problem with Minimal Summarized Rank via the Cross-Entropy Method." In Evolutionary Learning and Optimization, 227–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12834-9_11.

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9

Xu, Yuhua, Zhan Gao, Jinlong Wang, and Qihui Wu. "Multichannel Opportunistic Spectrum Access in Fading Environment Using Optimal Stopping Rule." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 275–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29157-9_26.

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10

"Optimal Stopping Rules." In Natural Resource Economics, 249–72. Cambridge University Press, 2020. http://dx.doi.org/10.1017/9781108588928.008.

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Тези доповідей конференцій з теми "Optimal stopping rules"

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Grzybowski, Andrzej Z., and Alexander M. Korsunsky. "Optimal Stopping Rules For Some Blackjack Type Problems." In CURRENT THEMES IN ENGINEERING SCIENCE 2009: Selected Presentations at the World Congress on Engineering-2009. AIP, 2010. http://dx.doi.org/10.1063/1.3366517.

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Zhang, Qing, Caojin Zhang, and George Yin. "Near-optimal stopping rules for two-time-scale Markovian systems." In 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE, 2017. http://dx.doi.org/10.1109/cdc.2017.8263729.

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Peng, Kangjing, and Gang Xie. "The Optimal Spectrum Sensing Stopping Rules Considering Power Limitation in Cognitive Radio." In 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring). IEEE, 2019. http://dx.doi.org/10.1109/vtcspring.2019.8746384.

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Liao, Fei. "Notice of Violation of IEEE Publication Principles - Optimal stopping rules for proofreading." In 2010 3rd International Conference on Biomedical Engineering and Informatics (BMEI 2010). IEEE, 2010. http://dx.doi.org/10.1109/bmei.2010.5639679.

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Sofronov, Georgy Yu, and Tatiana V. Polushina. "Evaluating Optimal Stopping Rules in the Multiple Best Choice Problem using the Cross-Entropy Method." In Artificial Intelligence and Applications. Calgary,AB,Canada: ACTAPRESS, 2013. http://dx.doi.org/10.2316/p.2013.794-018.

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Polushina, T. V. "Estimating optimal stopping rules in the multiple best choice problem with minimal summarized rank via the Cross-Entropy method." In 2009 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2009. http://dx.doi.org/10.1109/cec.2009.4983142.

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Raskutti, Garvesh, Martin J. Wainwright, and Bin Yu. "Early stopping for non-parametric regression: An optimal data-dependent stopping rule." In 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2011. http://dx.doi.org/10.1109/allerton.2011.6120320.

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Vaid, Vertika, Aaqib Patel, and S. N. Merchant. "Optimal channel stopping rule under constrained conditions for CRNs." In 2014 Twentieth National Conference on Communications (NCC). IEEE, 2014. http://dx.doi.org/10.1109/ncc.2014.6811283.

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Fekom, Mathilde, Nicolas Vayatis, and Argyris Kalogeratos. "Optimal Multiple Stopping Rule for Warm-Starting Sequential Selection." In 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2019. http://dx.doi.org/10.1109/ictai.2019.00202.

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