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1

Borodin, Alexei. "Discrete gap probabilities and discrete Painlev� equations." Duke Mathematical Journal 117, no. 3 (April 2003): 489–542. http://dx.doi.org/10.1215/s0012-7094-03-11734-2.

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2

Buckley, J. J., and E. Eslami. "Uncertain probabilities I: the discrete case." Soft Computing - A Fusion of Foundations, Methodologies and Applications 7, no. 8 (August 1, 2003): 500–505. http://dx.doi.org/10.1007/s00500-002-0234-2.

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3

Kalwani, Manohar U., Robert J. Meyer, and Donald G. Morrison. "Benchmarks for Discrete Choice Models." Journal of Marketing Research 31, no. 1 (February 1994): 65–75. http://dx.doi.org/10.1177/002224379403100106.

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In assessing the performance of a choice model, we have to answer the question, “Compared with what?” Analyses of consumer brand choice data historically have measured fit by comparing a model's performance with that of a naive model that assumes a household's choice probability on each occasion equals the aggregate market share of each brand. The authors suggest that this benchmark could form an overly naive point of reference in assessing the fit of a choice model calibrated on scanner-panel data, or any repeated-measures analysis of choice. They propose that fairer benchmarks for discrete choice models in marketing should incorporate heterogeneity in consumer choice probabilities, evidence for which is by now well documented in the marketing literature. They use simulated data to compare the performance of parametric and nonparametric benchmark models, which allow for heterogeneity in consumer choice probabilities, with the performance of the aggregate share-based benchmark model, which assumes consumers are homogeneous in their choice probabilities. They also assess the performance of two previously published consumer behavior models against the proposed fairer benchmark models that allow for heterogeneity in consumer choice probabilities. They find that one provides a significantly better fit than their more conservative benchmark models and the other performs less favorably.
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4

Cai, Jun. "DISCRETE TIME RISK MODELS UNDER RATES OF INTEREST." Probability in the Engineering and Informational Sciences 16, no. 3 (May 22, 2002): 309–24. http://dx.doi.org/10.1017/s0269964802163030.

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Two discrete time risk models under rates of interest are introduced. Ruin probabilities in the two risk models are discussed. Stochastic inequalities for the ruin probabilities are derived by martingales and renewal recursive techniques. The inequalities can be used to evaluate the ruin probabilities as upper bounds. Numerical illustrations for these results are given.
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5

Klar, Bernhard. "BOUNDS ON TAIL PROBABILITIES OF DISCRETE DISTRIBUTIONS." Probability in the Engineering and Informational Sciences 14, no. 2 (April 2000): 161–71. http://dx.doi.org/10.1017/s0269964800142032.

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6

Gouweleeuw, Frank N., and Henk C. Tijms. "Computing Loss Probabilities in Discrete-Time Queues." Operations Research 46, no. 1 (February 1998): 149–54. http://dx.doi.org/10.1287/opre.46.1.149.

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7

Kuklinski, Parker. "Absorption probabilities of discrete quantum mechanical systems." Journal of Physics A: Mathematical and Theoretical 51, no. 40 (September 7, 2018): 405301. http://dx.doi.org/10.1088/1751-8121/aad871.

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8

Škulj, Damjan. "Discrete time Markov chains with interval probabilities." International Journal of Approximate Reasoning 50, no. 8 (September 2009): 1314–29. http://dx.doi.org/10.1016/j.ijar.2009.06.007.

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9

K?�?, O. "Envelopes of a simplex of discrete probabilities." Soft Computing - A Fusion of Foundations, Methodologies and Applications 7, no. 5 (April 1, 2003): 336–43. http://dx.doi.org/10.1007/s00500-002-0221-7.

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10

Dani, S. G., and M. McCrudden. "Infinitely divisible probabilities on discrete linear groups." Journal of Theoretical Probability 9, no. 1 (January 1996): 215–29. http://dx.doi.org/10.1007/bf02213741.

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11

Sudhesh, Ramupillai, and Arumugam Vaithiyanathan. "Analysis of state-dependent discrete-time queue with system disaster." RAIRO - Operations Research 53, no. 5 (October 28, 2019): 1915–27. http://dx.doi.org/10.1051/ro/2018078.

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An explicit expression for time-dependent system size probabilities is obtained for the general state-dependent discrete-time queue with system disaster. Using generating function for the nth state transient probabilities, the underlying difference equation of system size probabilities are transformed into three-term recurrence relation which is then expressed as a continued fraction. The continued fractions are converted into formal power series which yield the time-dependent system size probabilities in closed form. Further, the busy period distribution is obtained for the considered model. As a special case, the system size probabilities and busy period distribution of Geo/Geo/1 queue are deduced. Finally, numerical illustrations are presented to visualize the system effect for various values of the parameters.
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12

SANTOS, A. L. DOS, L. P. L. DE OLIVEIRA, B. E. J. BODMANN, and M. T. VILHENA. "A FRACTAL-DISCRETE SCHEME FOR COSMIC PARTICLE ACCELERATION." International Journal of Modern Physics D 16, no. 02n03 (February 2007): 521–26. http://dx.doi.org/10.1142/s0218271807010341.

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The present article is an attempt to provide a parametrization for particle acceleration probabilities in the very high energy range combining a discrete fractal scheme for interaction probabilities and the observational fact of a power law energy spectrum for cosmic ray particles.
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13

GOMES, DIOGO A., NARA JUNG, and ARTUR O. LOPES. "MINIMAX PROBABILITIES FOR AUBRY–MATHER PROBLEMS." Communications in Contemporary Mathematics 12, no. 05 (October 2010): 789–813. http://dx.doi.org/10.1142/s0219199710004019.

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In this paper, we study minimax Aubry–Mather measures and its main properties. We consider first the discrete time problem and then the continuous time case. In the discrete time problem, we establish existence, study some of the main properties using duality theory and present some examples. In the continuous time case, we establish both existence and non-existence results. First, we give some examples showing that in continuous time stationary minimax Mather measures are either trivial or fail to exist. A more natural definition in continuous time are T-periodic minimax Mather measures. We give a complete characterization of these measures and discuss several examples.
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14

Henderson, W., and P. G. Taylor. "Discrete-time queueing networks with geometric release probabilities." Advances in Applied Probability 24, no. 01 (March 1992): 229–33. http://dx.doi.org/10.1017/s0001867800024289.

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This note is concerned with the continuing misconception that a discrete-time network of queues, with independent customer routing and the number of arrivals and services in a time interval following geometric and truncated geometric distributions respectively, has a product-form equilibrium distribution.
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15

Henderson, W., and P. G. Taylor. "Discrete-time queueing networks with geometric release probabilities." Advances in Applied Probability 24, no. 1 (March 1992): 229–33. http://dx.doi.org/10.2307/1427741.

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This note is concerned with the continuing misconception that a discrete-time network of queues, with independent customer routing and the number of arrivals and services in a time interval following geometric and truncated geometric distributions respectively, has a product-form equilibrium distribution.
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16

Schäl, Manfred. "Control of ruin probabilities by discrete-time investments." Mathematical Methods of Operations Research 62, no. 1 (September 2005): 141–58. http://dx.doi.org/10.1007/s00186-005-0445-2.

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17

Lefebvre, Mario, and Jean-Luc Guilbault. "First Hitting Place Probabilities for a Discrete Version of the Ornstein-Uhlenbeck Process." International Journal of Mathematics and Mathematical Sciences 2009 (2009): 1–12. http://dx.doi.org/10.1155/2009/909835.

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A Markov chain with state space{0,…,N}and transition probabilities depending on the current state is studied. The chain can be considered as a discrete Ornstein-Uhlenbeck process. The probability that the process hitsNbefore 0 is computed explicitly. Similarly, the probability that the process hitsNbefore−Mis computed in the case when the state space is{−M,…,0,…,N}and the transition probabilitiespi,i+1are not necessarily the same wheniis positive andiis negative.
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18

Wan, Xiongbo, Chuanyu Ren, and Jianqi An. "Robust Stability of Discrete-Time Randomly Switched Delayed Genetic Regulatory Networks with Known Sojourn Probabilities." Journal of Advanced Computational Intelligence and Intelligent Informatics 20, no. 7 (December 20, 2016): 1094–102. http://dx.doi.org/10.20965/jaciii.2016.p1094.

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This study investigates stability problems related to discrete-time randomly switched genetic regulatory networks (GRNs) with time-varying delays. A new discrete-time randomly switched GRN model with known sojourn probabilities is proposed. By utilizing the discrete Wirtinger-based inequality and a newly proposed constraint condition on the feedback regulatory function, which have not been fully used in stability analysis of discrete-time GRNs, we establish delay-dependent stability and robust stability criteria. These criteria possess the sojourn probabilities of randomly switched GRNs. Two numerical examples are provided to demonstrate the effectiveness of the established results.
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19

Mercer, Joseph O. "Some Surprising Probabilities from Bingo." Mathematics Teacher 86, no. 9 (December 1993): 726–31. http://dx.doi.org/10.5951/mt.86.9.0726.

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It is human nature to look for easy ways to get ahead. As teachers we would hope that studying probability would help our students understand why gambling is not such a way. Since bingo is a form of legalized gambling that is familiar to almost everyone, the game is worth spending some time to analyze. In fact, most of the fundamental concepts from discrete-probability theory can be covered by studying bingo
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20

Miyazawa, Masakiyo, and Yiqiang Q. Zhao. "The stationary tail asymptotics in the GI/G/1-type queue with countably many background states." Advances in Applied Probability 36, no. 04 (December 2004): 1231–51. http://dx.doi.org/10.1017/s0001867800013380.

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We consider the asymptotic behaviour of the stationary tail probabilities in the discrete-time GI/G/1-type queue with countable background state space. These probabilities are presented in matrix form with respect to the background state space, and shown to be the solution of a Markov renewal equation. Using this fact, we consider their decay rates. Applying the Markov renewal theorem, it is shown that certain reasonable conditions lead to the geometric decay of the tail probabilities as the level goes to infinity. We exemplify this result using a discrete-time priority queue with a single server and two types of customer.
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21

Miyazawa, Masakiyo, and Yiqiang Q. Zhao. "The stationary tail asymptotics in the GI/G/1-type queue with countably many background states." Advances in Applied Probability 36, no. 4 (December 2004): 1231–51. http://dx.doi.org/10.1239/aap/1103662965.

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We consider the asymptotic behaviour of the stationary tail probabilities in the discrete-time GI/G/1-type queue with countable background state space. These probabilities are presented in matrix form with respect to the background state space, and shown to be the solution of a Markov renewal equation. Using this fact, we consider their decay rates. Applying the Markov renewal theorem, it is shown that certain reasonable conditions lead to the geometric decay of the tail probabilities as the level goes to infinity. We exemplify this result using a discrete-time priority queue with a single server and two types of customer.
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22

Charnsethi, Peerayuth. "Computational Discrete Time Markov Chain with Correlated Transition Probabilities." Journal of Mathematics and Statistics 2, no. 4 (April 1, 2006): 457–59. http://dx.doi.org/10.3844/jmssp.2006.457.459.

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23

Grigutis, Andrius, Agneška Korvel, and Jonas Šiaulys. "Ruin Probabilities of a Discrete-time Multi-risk Model." Information Technology And Control 44, no. 4 (December 16, 2015): 367–79. http://dx.doi.org/10.5755/j01.itc.44.4.8635.

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In this work, we investigate a multi-risk model describing insurance business with two or more independent series of claim amounts. Each series of claim amounts consists of independent nonnegative random variables. Claims of each series occur periodically with some fixed inter-arrival time. Claim amounts occur until they can be compensated by a common premium rate and the initial insurer's surplus. In this article, wederive a recursive formula for calculation of finite-time ruin probabilities. In the case of bi-risk model, we present a procedure to calculate the ultimate ruin probability. We add several numerical examples illustrating application of the derived formulas.DOI: http://dx.doi.org/10.5755/j01.itc.44.4.8635
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24

Dubins, Lester E. "Discrete Red-and-Black with Fortune-Dependent Win Probabilities." Probability in the Engineering and Informational Sciences 12, no. 4 (October 1998): 417–24. http://dx.doi.org/10.1017/s0269964800005295.

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For discrete versions of red-and-black with a goal, for timid play to be optimal, it suffices, but is not necessary, that no win probability be less than one-half. A condition that is both necessary and sufficient is provided.
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25

Mattner, Lutz, and Bero Roos. "Maximal probabilities of convolution powers of discrete uniform distributions." Statistics & Probability Letters 78, no. 17 (December 2008): 2992–96. http://dx.doi.org/10.1016/j.spl.2008.05.005.

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26

Chen, Mi, Kam Chuen Yuen, and Junyi Guo. "Survival probabilities in a discrete semi-Markov risk model." Applied Mathematics and Computation 232 (April 2014): 205–15. http://dx.doi.org/10.1016/j.amc.2014.01.057.

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27

Cossette, Hélène, David Landriault, and Etienne Marceau. "Ruin probabilities in the discrete time renewal risk model." Insurance: Mathematics and Economics 38, no. 2 (April 2006): 309–23. http://dx.doi.org/10.1016/j.insmatheco.2005.09.005.

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28

Wu, Xueyuan, Mi Chen, Junyi Guo, and Can Jin. "On a discrete-time risk model with claim correlated premiums." Annals of Actuarial Science 9, no. 2 (July 21, 2015): 322–42. http://dx.doi.org/10.1017/s1748499515000032.

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AbstractThis paper proposes a discrete-time risk model that has a certain type of correlation between premiums and claim amounts. It is motivated by the well-known bonus-malus system (also known as the no claims discount) in the car insurance industry. Such a system penalises policyholders at fault in accidents by surcharges, and rewards claim-free years by discounts. For simplicity, only up to three levels of premium are considered in this paper and recursive formulae are derived to calculate the ultimate ruin probabilities. Explicit expressions of ruin probabilities are obtained in a simplified case. The impact of the proposed correlation between premiums and claims on ruin probabilities is examined through numerical examples. In the end, the joint probability of ruin and deficit at ruin is also considered.
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29

NAGY, GÁBOR V., and VILMOS TOTIK. "A Convexity Property of Discrete Random Walks." Combinatorics, Probability and Computing 25, no. 6 (March 31, 2016): 928–40. http://dx.doi.org/10.1017/s0963548316000109.

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We establish a convexity property for the hitting probabilities of discrete random walks in ${\mathbb Z}^d$ (discrete harmonic measures). For d = 2 this implies a recent result on the convexity of the density of certain harmonic measures.
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30

Hu, Linmin, and Rui Peng. "Reliability modeling for a discrete time multi-state system with random and dependent transition probabilities." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 233, no. 5 (January 20, 2019): 747–60. http://dx.doi.org/10.1177/1748006x18819920.

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In a random environment, state transition probabilities of a multi-state system can change as the environment changes. Thus, a dynamic reliability model with random and dependent transition probabilities is developed for non-repairable discrete-time multi-state system in this article. The dependence among the random state transition probabilities of the system is modeled by a copula function. By probability argument and random process theory, we obtain explicit expressions of some reliability characteristics and joint survival function of random time spent by the system in all working states (partially and completely working states). A special case is considered when the state transition probabilities are dependent random variables with power distribution, and the dependence structure is modeled by Farlie–Gumbel–Morgenstern copula. Numerical examples are also presented to demonstrate the developed model and perform a comparison for the models with random and fixed transition probabilities.
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31

Diasparra, Maikol A., and Rosario Romera. "Bounds for the Ruin Probability of a Discrete-Time Risk Process." Journal of Applied Probability 46, no. 01 (March 2009): 99–112. http://dx.doi.org/10.1017/s0021900200005258.

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We consider a discrete-time risk process driven by proportional reinsurance and an interest rate process. We assume that the interest rate process behaves as a Markov chain. To reduce the risk of ruin, we may reinsure a part or even all of the reserve. Recursive and integral equations for ruin probabilities are given. Generalized Lundberg inequalities for the ruin probabilities are derived given a stationary policy. To illustrate these results, a numerical example is included.
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32

Diasparra, Maikol A., and Rosario Romera. "Bounds for the Ruin Probability of a Discrete-Time Risk Process." Journal of Applied Probability 46, no. 1 (March 2009): 99–112. http://dx.doi.org/10.1239/jap/1238592119.

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We consider a discrete-time risk process driven by proportional reinsurance and an interest rate process. We assume that the interest rate process behaves as a Markov chain. To reduce the risk of ruin, we may reinsure a part or even all of the reserve. Recursive and integral equations for ruin probabilities are given. Generalized Lundberg inequalities for the ruin probabilities are derived given a stationary policy. To illustrate these results, a numerical example is included.
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33

Konstantopoulos, Takis, and Michael Zazanis. "A discrete-time proof of Neveu's exchange formula." Journal of Applied Probability 32, no. 4 (December 1995): 917–21. http://dx.doi.org/10.2307/3215204.

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Neveu's exchange formula relates the Palm probabilities with respect to two jointly stationary simple point processes. We give a new proof of the exchange formula by using a simple result from discrete time stationary stochastic processes.
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34

Konstantopoulos, Takis, and Michael Zazanis. "A discrete-time proof of Neveu's exchange formula." Journal of Applied Probability 32, no. 04 (December 1995): 917–21. http://dx.doi.org/10.1017/s0021900200103389.

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Neveu's exchange formula relates the Palm probabilities with respect to two jointly stationary simple point processes. We give a new proof of the exchange formula by using a simple result from discrete time stationary stochastic processes.
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35

Lefèvre, Claude, and Stéphane Loisel. "Finite-Time Ruin Probabilities for Discrete, Possibly Dependent, Claim Severities." Methodology and Computing in Applied Probability 11, no. 3 (February 26, 2009): 425–41. http://dx.doi.org/10.1007/s11009-009-9123-9.

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36

Gajek, Lesław, and Marcin Rudź. "Sharp approximations of ruin probabilities in the discrete time models." Scandinavian Actuarial Journal 2013, no. 5 (September 2013): 352–82. http://dx.doi.org/10.1080/03461238.2011.618761.

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37

Retzlaff, T. M. "Decay of Concentration Functions for Adapted Probabilities on Discrete Groups." Journal of Theoretical Probability 17, no. 4 (October 2004): 1031–40. http://dx.doi.org/10.1007/s10959-004-0589-7.

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38

Krishna, M., and Manjunath Krishnapur. "Persistence probabilities in centered, stationary, Gaussian processes in discrete time." Indian Journal of Pure and Applied Mathematics 47, no. 2 (June 2016): 183–94. http://dx.doi.org/10.1007/s13226-016-0183-6.

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39

PATEL, MINNIE H., and H. S. JACOB TSAO. "FORWARD APPORTIONMENT OF CENSORED COUNTS FOR DISCRETE NONPARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION OF FAILURE PROBABILITIES." International Journal of Reliability, Quality and Safety Engineering 16, no. 03 (June 2009): 213–34. http://dx.doi.org/10.1142/s0218539309003368.

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Empirical cumulative lifetime distribution function is often required for selecting lifetime distribution. When some test items are censored from testing before failure, this function needs to be estimated, often via the approach of discrete nonparametric maximum likelihood estimation (DN-MLE). In this approach, this empirical function is expressed as a discrete set of failure-probability estimates. Kaplan and Meier used this approach and obtained a product-limit estimate for the survivor function, in terms exclusively of the hazard probabilities, and the equivalent failure-probability estimates. They cleverly expressed the likelihood function as the product of terms each of which involves only one hazard probability ease of derivation, but the estimates for failure probabilities are complex functions of hazard probabilities. Because there are no closed-form expressions for the failure probabilities, the estimates have been calculated numerically. More importantly, it has been difficult to study the behavior of the failure probability estimates, e.g., the standard errors, particularly when the sample size is not very large. This paper first derives closed-form expressions for the failure probabilities. For the special case of no censoring, the DN-MLE estimates for the failure probabilities are in closed forms and have an obvious, intuitive interpretation. However, the Kaplan–Meier failure-probability estimates for cases involving censored data defy interpretation and intuition. This paper then develops a simple algorithm that not only produces these estimates but also provides a clear, intuitive justification for the estimates. We prove that the algorithm indeed produces the DN-MLE estimates and demonstrate numerically their equivalence to the Kaplan–Meier-based estimates. We also provide an alternative algorithm.
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40

Moggi, Eugenio, Walid Taha, and Johan Thunberg. "Sound Over-Approximation of Probabilities." Acta Cybernetica 24, no. 3 (March 16, 2020): 269–85. http://dx.doi.org/10.14232/actacyb.24.3.2020.2.

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Safety analysis of high confidence systems requires guaranteed bounds on the probability of events of interest. Establishing the correctness of algorithms that compute such bounds is challenging. We address this problem in three steps. First, we use monadic transition systems (MTS) in the category of sets as a general framework for modeling discrete time systems. MTS can capture different types of system behaviors, but here we focus on a combination of non-deterministic and probabilistic behaviors that arises often when modeling complex systems. Second, we use the category of posets and monotonic maps as general setting to define and compare approximations. In particular, for the MTS of interest, we consider approximations of their configurations based on complete lattices of interval probabilities. Third, we obtain an algorithm that computes over-approximations of system configurations after a finite number of steps, by restricting to finite lattices.
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41

Shafiqul Islam, Md, Pawel Góra, and Abraham Boyarsky. "A generalization of Straube's theorem: existence of absolutely continuous invariant measures for random maps." Journal of Applied Mathematics and Stochastic Analysis 2005, no. 2 (January 1, 2005): 133–41. http://dx.doi.org/10.1155/jamsa.2005.133.

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A random map is a discrete-time dynamical system in which one of a number of transformations is randomly selected and applied at each iteration of the process. In this paper, we study random maps. The main result provides a necessary and sufficient condition for the existence of absolutely continuous invariant measure for a random map with constant probabilities and position-dependent probabilities.
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42

Huillet, Thierry E. "A Duality Approach to the Genealogies of Discrete Nonneutral Wright-Fisher Models." Journal of Probability and Statistics 2009 (2009): 1–22. http://dx.doi.org/10.1155/2009/714701.

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Discrete ancestral problems arising in population genetics are investigated. In the neutral case, the duality concept has been proved of particular interest in the understanding of backward in time ancestral process from the forward in time branching population dynamics. We show that duality formulae still are of great use when considering discrete nonneutral Wright-Fisher models. This concerns a large class of nonneutral models with completely monotone (CM) bias probabilities. We show that most classical bias probabilities used in the genetics literature fall within this CM class or are amenable to it through some “reciprocal mechanism” which we define. Next, using elementary algebra on CM functions, some suggested novel evolutionary mechanisms of potential interest are introduced and discussed.
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43

Sevastyanov, B. A. "Final probabilities for modified branching processes." Discrete Mathematics and Applications 12, no. 1 (January 1, 2002): 1–8. http://dx.doi.org/10.1515/dma-2002-0102.

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44

Kahn, Jeff, and Yang Yu. "Log-Concave Functions And Poset Probabilities." COMBINATORICA 18, no. 1 (January 1998): 85–99. http://dx.doi.org/10.1007/pl00009812.

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45

Bernardi, Enrico, and Silvia Romagnoli. "A distorted copula-based evolution model: risks’ aggregation in a Bonus–Malus migration system." Soft Computing 25, no. 17 (June 28, 2021): 11845–63. http://dx.doi.org/10.1007/s00500-021-05974-0.

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AbstractIn this paper, we put forward a new model to compute the loss distribution of an automobile insurance company’s portfolio evolving by a bonus–malus system. We allow for a continuous evolution of the demographic-economic system based on a migration’s rule which is refreshed in discrete time, i.e., at the monitoring times. Therefore, the migration’s probabilities are discretely updated through a technique based on the combinatorial distributions of claims’ arrival in the rating classes. This technique is hierarchical copula-based, a natural tool permitting us to represent the co-movement between claims’ arrivals and distorted due to the formalization of an arrival policy of claims, that restricts the set of combinatorial distributions to those representing the most probable scenarios, therefore distorting the loss function. At every monitoring date, the copula-based model computes the migration’s probabilities and the loss function which accommodates for a discrete-time dynamic of the claims’ reserving and the capital requirements. An empirical application, the evaluation of the claims’ reserving and the capital requirements for different kinds of hierarchies are analyzed, with real data originating with the General Insurance Association of Singapore.
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46

Lin, Hongsheng, Ying Li, and Guoliang Wang. "H∞Control of Singular Markovian Jump Systems with Bounded Transition Probabilities." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/495194.

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This paper discussesH∞control problems of continuous-time and discrete-time singular Markovian jump systems (SMJSs) with bounded transition probabilities. Improved sufficient conditions for continuous-time SMJSs to be regular, impulse free, and stochastically stable withγ-disturbance attenuation are established via less conservative inequality to estimate the transition jump rates, so are the discrete-time SMJSs. With the obtained conditions, the design of a state feedback controller which ensures the resulting closed-loop system to be stochastically admissible and withH∞performance is given in terms of linear matrix inequalities (LMIs). Finally, illustrative examples are presented to show the effectiveness and the benefits of the proposed approaches.
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47

Glaz, Joseph, and Joseph I. Naus. "Tight Bounds and Approximations for Scan Statistic Probabilities for Discrete Data." Annals of Applied Probability 1, no. 2 (May 1991): 306–18. http://dx.doi.org/10.1214/aoap/1177005940.

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48

Lee, Kong Aik, Chang Huai You, Haizhou Li, Tomi Kinnunen, and Khe Chai Sim. "Using Discrete Probabilities With Bhattacharyya Measure for SVM-Based Speaker Verification." IEEE Transactions on Audio, Speech, and Language Processing 19, no. 4 (May 2011): 861–70. http://dx.doi.org/10.1109/tasl.2010.2064308.

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49

Hu, Jie, Anton Dzhamay, and Yang Chen. "Gap probabilities in the Laguerre unitary ensemble and discrete Painlevé equations." Journal of Physics A: Mathematical and Theoretical 53, no. 35 (August 18, 2020): 354003. http://dx.doi.org/10.1088/1751-8121/ab9f70.

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50

Claassen, Roger, and Abebayehu Tegene. "Agricultural Land Use Choice: A Discrete Choice Approach." Agricultural and Resource Economics Review 28, no. 1 (April 1999): 26–36. http://dx.doi.org/10.1017/s1068280500000940.

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Abstract:
A discrete choice model and site-specific data are used to analyze land use choices between crop production and pasture in the Corn Belt. The results show that conversion probabilities depend on relative returns, land quality, and government policy. In general it is found that landowners are less inclined to remove land from crop production than to convert land to crop production.
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