Optimal Strategies for Stopping Near the Top of a Sequence
In Chapter 1 the classical secretary problem is introduced. Chapters 2 and 3 are variations of this problem. Chapter 2, discusses the problem of maximizing the probability of stopping with one of the two highest values in a Bernoulli random walk with arbitrary parameter p and finite time horizon n....
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ndltd-unt.edu-info-ark-67531-metadc8228122020-07-15T07:09:31Z Optimal Strategies for Stopping Near the Top of a Sequence Islas Anguiano, Jose Angel optimal stopping max selection classical secretary problem Optimal stopping (Mathematical statistics) Secretary problem (Probability theory) Random walks (Mathematics) In Chapter 1 the classical secretary problem is introduced. Chapters 2 and 3 are variations of this problem. Chapter 2, discusses the problem of maximizing the probability of stopping with one of the two highest values in a Bernoulli random walk with arbitrary parameter p and finite time horizon n. The optimal strategy (continue or stop) depends on a sequence of threshold values (critical probabilities) which has an oscillating pattern. Several properties of this sequence have been proved by Dr. Allaart. Further properties have been recently proved. In Chapter 3, a gambler will observe a finite sequence of continuous random variables. After he observes a value he must decide to stop or continue taking observations. He can play two different games A) Win at the maximum or B) Win within a proportion of the maximum. In the first section the sequence to be observed is independent. It is shown that for each n>1, theoptimal win probability in game A is bounded below by (1-1/n)^{n-1}. It is accomplished by reducing the problem to that of choosing the maximum of a special sequence of two-valued random variables and applying the sum-the-odds theorem of Bruss (2000). Secondly, it is assumed the sequence is i.i.d. The best lower bounds are provided for the winning probabilities in game B given any continuous distribution. These bounds are the optimal win probabilities of a game A which was examined by Gilbert and Mosteller (1966). University of North Texas Allaart, Pieter C. Song, Kai-Sheng Quintanilla, John Monticino, Michael G. 2015-12 Thesis or Dissertation iv, 95 pages : illustrations Text https://digital.library.unt.edu/ark:/67531/metadc822812/ ark: ark:/67531/metadc822812 English Public Islas Anguiano, Jose Angel Copyright Copyright is held by the author, unless otherwise noted. All rights Reserved. |
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optimal stopping max selection classical secretary problem Optimal stopping (Mathematical statistics) Secretary problem (Probability theory) Random walks (Mathematics) |
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optimal stopping max selection classical secretary problem Optimal stopping (Mathematical statistics) Secretary problem (Probability theory) Random walks (Mathematics) Islas Anguiano, Jose Angel Optimal Strategies for Stopping Near the Top of a Sequence |
description |
In Chapter 1 the classical secretary problem is introduced. Chapters 2 and 3 are variations of this problem. Chapter 2, discusses the problem of maximizing the probability of stopping with one of the two highest values in a Bernoulli random walk with arbitrary parameter p and finite time horizon n. The optimal strategy (continue or stop) depends on a sequence of threshold values (critical probabilities) which has an oscillating pattern. Several properties of this sequence have been proved by Dr. Allaart. Further properties have been recently proved. In Chapter 3, a gambler will observe a finite sequence of continuous random variables. After he observes a value he must decide to stop or continue taking observations. He can play two different games A) Win at the maximum or B) Win within a proportion of the maximum. In the first section the sequence to be observed is independent. It is shown that for each n>1, theoptimal win probability in game A is bounded below by (1-1/n)^{n-1}. It is accomplished by reducing the problem to that of choosing the maximum of a special sequence of two-valued random variables and applying the sum-the-odds theorem of Bruss (2000). Secondly, it is assumed the sequence is i.i.d. The best lower bounds are provided for the winning probabilities in game B given any continuous distribution. These bounds are the optimal win probabilities of a game A which was examined by Gilbert and Mosteller (1966). |
author2 |
Allaart, Pieter C. |
author_facet |
Allaart, Pieter C. Islas Anguiano, Jose Angel |
author |
Islas Anguiano, Jose Angel |
author_sort |
Islas Anguiano, Jose Angel |
title |
Optimal Strategies for Stopping Near the Top of a Sequence |
title_short |
Optimal Strategies for Stopping Near the Top of a Sequence |
title_full |
Optimal Strategies for Stopping Near the Top of a Sequence |
title_fullStr |
Optimal Strategies for Stopping Near the Top of a Sequence |
title_full_unstemmed |
Optimal Strategies for Stopping Near the Top of a Sequence |
title_sort |
optimal strategies for stopping near the top of a sequence |
publisher |
University of North Texas |
publishDate |
2015 |
url |
https://digital.library.unt.edu/ark:/67531/metadc822812/ |
work_keys_str_mv |
AT islasanguianojoseangel optimalstrategiesforstoppingnearthetopofasequence |
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1719329099604819968 |