Regret and Behavior: Comment on Zeelenberg and Pieters.

Science.gov (United States)

Roese, Neal J; Summerville, Amy; Fessel, Florian

2007-01-01

Zeelenberg and Pieter's (2007) regret regulation theory 1.0 offers a synthesis that brings together concepts spanning numerous literatures. We have no substantive disagreement with their theory, but instead offer 3 observations to further aid regret researchers studying consumer decision making. First, the overall arch of any regret theory must be situated within an understanding of behavior regulation. Second, the distinction between regrets of action versus inaction is best understood in terms of motivational implications, particularly with regard to Higgin's (1998) distinction between promotion and prevention focus. Third, the opportunity principle offers a particularly clear means of summarizing the regulatory consequences of the regret experience. Regret is an emotion pivotal for decision making, and its cognitive underpinning has and continues to be elucidated in research focusing on counterfactual thinking.

Understanding others' regret: a FMRI study.

Directory of Open Access Journals (Sweden)

Nicola Canessa

Full Text Available Previous studies showed that the understanding of others' basic emotional experiences is based on a "resonant" mechanism, i.e., on the reactivation, in the observer's brain, of the cerebral areas associated with those experiences. The present study aimed to investigate whether the same neural mechanism is activated both when experiencing and attending complex, cognitively-generated, emotions. A gambling task and functional-Magnetic-Resonance-Imaging (fMRI were used to test this hypothesis using regret, the negative cognitively-based emotion resulting from an unfavorable counterfactual comparison between the outcomes of chosen and discarded options. Do the same brain structures that mediate the experience of regret become active in the observation of situations eliciting regret in another individual? Here we show that observing the regretful outcomes of someone else's choices activates the same regions that are activated during a first-person experience of regret, i.e. the ventromedial prefrontal cortex, anterior cingulate cortex and hippocampus. These results extend the possible role of a mirror-like mechanism beyond basic emotions.

Supporting English Language Learners in Math Class, Grades K-2

Science.gov (United States)

Bresser, Rusty; Melanese, Kathy; Sphar, Christine

2009-01-01

More than 10 percent of the students in our nation's public schools are English language learners, and this number grows each year. Many of these students are falling behind in math. "Supporting English Language Learners in Math Class, Grades K-2" outlines the challenges ELL students face when learning math and provides a wealth of specific…

Anticipated regret and health behavior: A meta-analysis.

Science.gov (United States)

Brewer, Noel T; DeFrank, Jessica T; Gilkey, Melissa B

2016-11-01

Risk beliefs are central to most theories of health behavior, yet many unanswered questions remain about an increasingly studied risk construct, anticipated regret. The authors sought to better understand anticipated regret's role in motivating health behaviors. The authors systematically searched electronic databases for studies of anticipated regret and behavioral intentions or health behavior. They used random effects meta-analysis to synthesize effect sizes from 81 studies (n = 45,618). Anticipated regret was associated with both intentions (r+ = .50, p emotions and risk appraisals. Anticipated inaction regret has a stronger and more stable association with health behavior than previously thought. The field should give greater attention to understanding how anticipated regret differs from similar constructs, its role in health behavior theory, and its potential use in health behavior interventions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Integrated Transport Planning Framework Involving Combined Utility Regret Approach

DEFF Research Database (Denmark)

Wang, Yang; Monzon, Andres; Di Ciommo, Floridea

2014-01-01

Sustainable transport planning requires an integrated approach involving strategic planning, impact analysis, and multicriteria evaluation. This study aimed at relaxing the utility-based decision-making assumption by newly embedding anticipated-regret and combined utility regret decision mechanisms...... in a framework for integrated transport planning. The framework consisted of a two-round Delphi survey, integrated land use and transport model for Madrid, and multicriteria analysis. Results show that (a) the regret-based ranking has a similar mean but larger variance than the utility-based ranking does, (b......) the least-regret scenario forms a compromise between the desired and the expected scenarios, (c) the least-regret scenario can lead to higher user benefits in the short term and lower user benefits in the long term, (d) the utility-based, the regret-based, and the combined utility- and regret...

Markov processes from K. Ito's perspective (AM-155)

CERN Document Server

Stroock, Daniel W

2003-01-01

Kiyosi Itô''s greatest contribution to probability theory may be his introduction of stochastic differential equations to explain the Kolmogorov-Feller theory of Markov processes. Starting with the geometric ideas that guided him, this book gives an account of Itô''s program. The modern theory of Markov processes was initiated by A. N. Kolmogorov. However, Kolmogorov''s approach was too analytic to reveal the probabilistic foundations on which it rests. In particular, it hides the central role played by the simplest Markov processes: those with independent, identically distributed incremen

Dependability estimation for non-Markov consecutive-k-out-of-n: F repairable systems by fast simulation

International Nuclear Information System (INIS)

Xiao Gang; Li Zhizhong; Li Ting

2007-01-01

A model of consecutive-k-out-of-n: F repairable system with non-exponential repair time distribution and (k-1)-step Markov dependence is introduced in this paper along with algorithms of three Monte Carlo methods, i.e. importance sampling, conditional expectation estimation and combination of the two methods, to estimate dependability of the non-Markov model including reliability, transient unavailability, MTTF, and MTBF. A numerical example is presented to demonstrate the efficiencies of above methods. The results show that combinational method has the highest efficiency for estimation of unreliability and unavailability, while conditional expectation estimation is the most efficient method for estimation of MTTF and MTBF. Conditional expectation estimation seems to have overall higher speedups in estimating dependability of such systems

Using Regrets to Elicit Behavior Change in Student-Athletes

Science.gov (United States)

Madrigal, Leilani A.; Robbins, Jamie E.; Stanley, Christopher

2017-01-01

The main objective of this article is to support the notion of regret as a useful tool rather than merely a negative emotion. The article introduces means for using feelings of regret to change past behaviors, increase motivation to reach goals, and minimize future regrets in athletes and teams.

Regret of Multi-Channel Bandit Game in Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Ma Jun

2016-01-01

Full Text Available The problem of how to evaluate the rate of convergence to Nash equilibrium solutions in the process of channel selection under incomplete information is studied. In this paper, the definition of regret is used to reflect the convergence rates of online algorithms. The process of selecting an idle channel for each secondary user is modeled as a multi-channel bandit game. The definition of the maximal averaged regret is given. Two existing online learning algorithms are used to obtain the Nash equilibrium for each SU. The maximal averaged regrets are used to evaluate the performances of online algorithms. When there is a pure strategy Nash equilibrium in the multi-channel bandit game, the maximal averaged regrets are finite. A cooperation mechanism is also needed in the process of calculating the maximal averaged regrets. Simulation results show the maximal averaged regrets are finite and the online algorithm with greater convergence rate has less maximal averaged regrets.

The value of adaptive regret management in retirement.

Science.gov (United States)

Farquhar, Jamie C; Wrosch, Carsten; Pushkar, Dolores; Li, Karen Z H

2013-01-01

This 3-year longitudinal study examined the associations between regret management, everyday activities, and retirement satisfaction among recent retirees. We hypothesized that the regulation of a severe life regret can facilitate activity engagement and retirement satisfaction, but only if retirees manage their regrets adaptively by either increasing effort and commitment when possessing favorable opportunities or disengaging when opportunity is unfavorable. Cross-sectional analyses demonstrated that the highest baseline levels of activity (e.g., volunteering, traveling) and retirement satisfaction were observed among participants who perceived favorable opportunities for addressing their life regrets and had high levels of engagement. Longitudinal analyses showed that this pattern was also associated with increases in activity engagement. In contrast, disengagement protected individuals with unfavorable opportunity from 3-year declines in retirement satisfaction. These findings indicate that adaptive regulation of regrets can both contribute to gains and prevent losses in the early stages of retirement, which may have lasting consequences on retirees' quality of life.

Myopic Regret Avoidance: Feedback Avoidance and Learning in Repeated Decision Making

Science.gov (United States)

Reb, Jochen; Connolly, Terry

2009-01-01

Decision makers can become trapped by "myopic regret avoidance" in which rejecting feedback to avoid short-term "outcome regret" (regret associated with counterfactual outcome comparisons) leads to reduced learning and greater long-term regret over continuing poor decisions. In a series of laboratory experiments involving repeated choices among…

Regret Aversion Bias dan Risk Tolerance Investor Muda Jakarta dan Surabaya

Directory of Open Access Journals (Sweden)

Yohnson Yohnson

2008-01-01

Full Text Available Investment decision behavior is an interesting topic in finance research. Bailey and Kinerson’s (2005 research found that individual risk tolerance and experienced regret significantly influenced investment decisions. Anticipation of potential future regret did not predict subsequent investment decision behavior. Specifically, this research also wants to know the effects of a person’s experienced regret and anticipated regret or the effects of individual risk tolerance on investment decision behavior in Jakarta and Surabaya. Respondent of this research is 323 students from UK Petra who represent young investors from Surabaya and students from UPH who represent young investors from Jakarta. The method of research is experimental study and the design of research is 2x2x2 (between subject with experienced regret (time deposit and stock as first variable, anticipated regret (time deposit and stock as second variable and risk tolerance (high and low as third variable This study finds that an individual risk tolerance significantly influences decisions. Regret aversion bias does not influence young investors in Indonesia. (We assume that it is because the character of Indonesian investors is different from foreign investors. The couse of this is supposedly the unique characteristics of Indonesian investors and the different view points between Indonesian investors and investors from other countries. Abstract in Bahasa Indonesia: Perilaku keputusan investasi sangat menarik untuk diteliti. Dalam penelitian Bailey dan Kinerson (2005 ditemukan risk tolerance dan experienced regret mempengaruhi keputusan investasi. Anticipated regret tidak dapat dipakai sebagai predictor perilaku keputusan investasi. Penelitian ini juga ingin mengetahui experienced regret, anticipated regret atau risk tolerance yang lebih mempengaruhi perilaku keputusan investasi di Jakarta dan Surabaya. Responden yang diteliti sebesar 323 mahasiswa berasal dari UK Petra yang mewakili

Regret in One-Shot and Recurrent Decisions: A Cautionary Tale

OpenAIRE

Imas, Alex; Lamé, Diego; Wilson, Alistair J.

2016-01-01

Under regret theory, decision-makers derive utility both from the outcome of their chosen action and the counterfactual. Evidence for anticipatory regret aversion has been found in oneshot settings, with ”regret lotteries” that always reveal outcomes, as a counterfactual on non-entry, being priced higher than comparable standard lotteries that only realize outcomes for entrants. However, as anticipation and realization of regret necessarily interact in dynamic settings, the predictions of reg...

Waves of regret: a meg study of emotion and decision-making.

Science.gov (United States)

Giorgetta, Cinzia; Grecucci, Alessandro; Bonini, Nicolao; Coricelli, Giorgio; Demarchi, Gianpaolo; Braun, Christoph; Sanfey, Alan G

2013-01-01

Recent fMRI studies have investigated brain activity involved in the feeling of regret and disappointment by manipulating the feedback participants saw after making a decision to play certain gambles: full-feedback (regret: participant sees the outcomes from both the chosen and unchosen gamble) vs. partial-feedback (disappointment: participant only sees the outcome from chosen gamble). However, regret and disappointment are also characterized by differential agency attribution: personal agency for regret, external agency for disappointment. In this study, we investigate the neural correlates of these two characterizations of regret and disappointment using magnetoencephalography (MEG). To do this, we experimentally induced each emotion by manipulating feedback (chosen gamble vs. unchosen gamble), agency (human vs. computer choice) and outcomes (win vs. loss) in a fully randomized design. At the behavioral level the emotional experience of regret and disappointment were indeed affected by both feedback and agency manipulations. These emotions also differentially affect subsequent choices, with regret leading to riskier behavior. At the neural level both feedback and agency affected the brain responses associated with regret and disappointment, demonstrating differential localization in the brain for each. Notably, feedback regret showed greater brain activity in the right anterior and posterior regions, with agency regret producing greater activity in the left anterior region. These findings extend the evidence for neural activity in processing both regret and disappointment by highlighting for the first time the respective importance of feedback and agency, as well as outlining the temporal dynamics of these emotions. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Reference-Dependent Regret Model for Deterministic Trade-off Studies

Energy Technology Data Exchange (ETDEWEB)

Kujawski, Edouard

2005-02-25

Today's typical multi-criteria decision analysis is based on classical expected utility theory that assumes a mythical ''Rational Individual'' immune to psychological influences such as anticipated regret. It is therefore in conflict with rational individuals who trade-off some benefits and forgo the alternative with the highest total classical utility for a more balanced alternative in order to reduce their levels of anticipated regret. This paper focuses on decision making under certainty. It presents a reference-dependent regret model (RDRM) in which the level of regret that an individual experiences depends on the absolute values rather than the differences of the utilities of the chosen and forgone alternatives. The RDRM best choice may differ from the conventional linear additive utility model, the analytic hierarchy process, and the regret theory of Bell and Loomes and Sugden. Examples are presented that indicate that RDRM is the better predictive descriptor for decision making under certainty. RDRM satisfies transitivity of the alternatives under pairwise comparisons and models rank reversal consistent with observed reasonable choices under dynamic or distinct situations. Like regret theory, the RDRM utilities of all the alternatives under consideration are interrelated. For complex trade-off studies regret is incorporated as an element of a cost-utility-regret analysis that characterizes each alternative in terms of its monetary cost, an aggregate performance utility, and a regret value. This provides decision makers adequate information to compare the alternatives and depending on their values they may trade-off some performance and/or cost to avoid high levels of regret. The result is a well-balanced alternative often preferred by reasonable decision makers to the optimal choice of classical multi-attribute utility analysis. The model can readily be extended to incorporate rejoicing to suit decision makers who seek it. The

The inaction effect in the psychology of regret.

Science.gov (United States)

Zeelenberg, Marcel; van de Bos, Kees; van Dijk, Eric; Pieters, Rik

2002-03-01

Previous research showed that decisions to act (i.e., actions) produce more regret than decisions not to act (i.e., inactions). This previous research focused on decisions made in isolation and ignored that decisions are often made in response to earlier outcomes. The authors show in 4 experiments that these prior outcomes may promote action and hence make inaction more abnormal. They manipulated information about a prior outcome. As hypothesized, when prior outcomes were positive or absent, people attributed more regret to action than to inaction. However, as predicted and counter to previous research, following negative prior outcomes, more regret was attributed to inaction, a finding that the authors label the inaction effect. Experiment 4, showing differential effects for regret and disappointment, demonstrates the need for emotion-specific predictions.

Avoidance of anticipated regret: the ordering of prostate-specific antigen tests.

Science.gov (United States)

Sorum, Paul C; Mullet, Etienne; Shim, Junseop; Bonnin-Scaon, Sylvie; Chasseigne, Gérard; Cogneau, Joël

2004-01-01

When making decisions, people are known to try to minimize the regret that would be provoked by unwanted consequences of these decisions. The authors explored the strength and determinants of such anticipated regret in a study of physicians' decisions to order prostate-specific antigen (PSA) tests. 32 US and 33 French primary care physicians indicated the likelihood they would order a PSA for 32 hypothetical men presenting for routine physical exams. They then indicated how much regret they would feel if they found advanced prostate cancer in 12 other patients for whom they had chosen not to order PSAs several years before. The latter patients differed according to age (55, 65, or 75 years), a prior request or not for PSA testing, and no or some irregularity of the prostate on the earlier rectal exam. ANOVA found that regret was higher when the patient had requested a PSA, the prostate was irregular, and the patient was younger. Shape had less effect when the patient had requested a PSA. US physicians had more regret than the French, patient request had a greater impact on the Americans, and increasing patient age reduced regret more among the French. In a 1-way correlation, the regret score was associated with the likelihood of ordering PSAs for both the French (r = 0.64, P regret score was the most important predictor of the likelihood of ordering a PSA (beta = 0.37, P Regret over failing to diagnose aggressive prostate cancer is associated with a policy of ordering PSAs. This regret appears to be culturally sensitive.

Applying the expectancy disconfirmation and regret theories to online consumer behavior.

Science.gov (United States)

Liao, Chechen; Liu, Chuang-Chun; Liu, Yu-Ping; To, Pui-Lai; Lin, Hong-Nan

2011-04-01

This study synthesizes the expectancy disconfirmation theory with empirical theories pertaining to customer regret in an e-commerce environment. The study begins by examining the roles that information quality (IQ), system quality (SYQ), and service quality (SEQ) play in determining customer regret and satisfaction. Then the consequences of regret and satisfaction on reuse intention are examined. Survey data collected from 445 respondents are analyzed using structural equation modeling with partial least squares (PLS-Graph 3.0) to provide support for the hypothesized links. Results show that IQ disconfirmation, SYQ disconfirmation and SEQ disconfirmation are related to regret and satisfaction. Both regret and satisfaction are related to reuse intention. In addition, satisfaction mediates the effect of regret on reuse intention. Based on these results, implications for theory and practice are discussed.

Perbedaan Post Purchase Regret Berdasarkan Perilaku Pada Konsumen Wanita

OpenAIRE

Fardhani, Diah

2014-01-01

Post purchase regret is a negative emotion of consumer after evaluating the purchase decision has been made, the evaluation is conducted based on the outcome and process of consumer decision making. This study was a comparative quantitative study aimed to determine differences on post purchase regret based on unplanned and substitute purchasing behavior. The research hypothesis was the differences in post purchase regret based on unplanned behavior and substitute purchasing. The study involve...

A random regret minimization model of travel choice

NARCIS (Netherlands)

Chorus, C.G.; Arentze, T.A.; Timmermans, H.J.P.

2008-01-01

Abstract This paper presents an alternative to Random Utility-Maximization models of travel choice. Our Random Regret-Minimization model is rooted in Regret Theory and provides several useful features for travel demand analysis. Firstly, it allows for the possibility that choices between travel

Anticipated Regret and Omission Bias in HPV Vaccination Decisions

DEFF Research Database (Denmark)

Jensen, Niels Holm

2017-01-01

This study investigated effects of anticipated regret on parents’ HPV vaccination intentions and effects of omission bias on HPV vaccination intentions and vaccine uptake. An online survey was completed by 851 parents of adolescent girls in Denmark, a country where HPV vaccine safety is currently...... heavily debated. Multivariate regression analyses revealed anticipated inaction regret as a significant positive predictor of vaccination intentions, and, anticipated action regret as a significant negative predictor of vaccination intentions. Multivariate analyses also revealed omission bias...... in a hypothetical vaccination vignette as a significant negative predictor of HPV vaccination intention as well as vaccine uptake. Finally, the study tested effects of anticipated regret and omission bias on evaluations of two extisting Danish pro-vaccine campaign videos. Here, the result revealed anticipated...

Regret salience and accountability in the decoy effect

Directory of Open Access Journals (Sweden)

Terry Connolly

2013-03-01

Full Text Available Two experiments examined the impact on the decoy effect of making salient the possibility of post-decision regret, a manipulation that has been shown in several earlier studies to stimulate critical examination and improvement of decision process. Experiment 1 (N = 62 showed that making regret salient eliminated the decoy effect in a personal preference task. Experiment 2 (N = 242 replicated this finding for a different personal preference task and for a prediction task. It also replicated previous findings that external accountability demands do not reduce, and may exacerbate, the decoy effect. We interpret both effects in terms of decision justification, with different justification standards operating for different audiences. The decoy effect, in this account, turns on accepting a weak justification, which may be seen as adequate for an external audience or one's own inattentive self but inadequate under the more critical review triggered by making regret possibilities salient. Seeking justification to others (responding to accountability demands thus maintains or exacerbates the decoy effect; seeking justification to oneself (responding to regret salience reduces or eliminates it. The proposed mechanism provides a theoretical account both of the decoy effect itself and of how regret priming provides an effective debiasing procedure for it.

Investigating the appraisal patterns of regret and disappointment

NARCIS (Netherlands)

van Dijk, W.W.; Zeelenberg, M.

2002-01-01

Regret and disappointment are the two emotions that are most closely linked to decision making. This study compares the appraisal patterns of the two emotions. This is done in the context of the related negative emotions anger and sadness. The results show clear differences between regret and

Sex Differences in Relationship Regret: The Role of Perceived Mate Characteristics

Directory of Open Access Journals (Sweden)

Susan Coats

2012-07-01

Full Text Available The current set of studies examined regret involving action and inaction in the realm of romantic relationships by testing whether such regret is associated with the characteristics of one's mate. In study 1, 394 participants reported on a previous casual sexual encounter, and in study 2, 358 participants reported on a previous romantic relationship. In both, instances of actual engagement and instances of passing up opportunities were studied. Study 3 was experimental and elicited reactions to hypothetical scenarios from 201 participants. Regret reported by men in both study 1 and study 2 varied as a function of the perceived attractiveness of the participants' actual and potential mate. Regret reported by women in study 2 varied as a function of the perceived stinginess of the participant's mate and perceived wealth of the participants' potential mate. Study 3 found that sex differences in type of regret (with men regretting inaction more than women occurred only when the mate presented in the scenario was described in ways consistent with mate preferences. Together these findings suggest that regret differs between the sexes in ways consistent with sex differences in mate preferences.

Regret and its avoidance: a neuroimaging study of choice behavior.

Science.gov (United States)

Coricelli, Giorgio; Critchley, Hugo D; Joffily, Mateus; O'Doherty, John P; Sirigu, Angela; Dolan, Raymond J

2005-09-01

Human decisions can be shaped by predictions of emotions that ensue after choosing advantageously or disadvantageously. Indeed, anticipating regret is a powerful predictor of future choices. We measured brain activity using functional magnetic resonance imaging (fMRI) while subjects selected between two gambles wherein regret was induced by providing information about the outcome of the unchosen gamble. Increasing regret enhanced activity in the medial orbitofrontal region, the anterior cingulate cortex and the hippocampus. Notably, across the experiment, subjects became increasingly regret-aversive, a cumulative effect reflected in enhanced activity within medial orbitofrontal cortex and amygdala. This pattern of activity reoccurred just before making a choice, suggesting that the same neural circuitry mediates direct experience of regret and its anticipation. These results demonstrate that medial orbitofrontal cortex modulates the gain of adaptive emotions in a manner that may provide a substrate for the influence of high-level emotions on decision making.

``Feeling more regret than I would have imagined''

Directory of Open Access Journals (Sweden)

Diego Fernandez-Duque

2008-08-01

Full Text Available People tend to overestimate emotional responses to future events. This study examined whether such affective forecasting errors occur for feelings of regret, as measured by self-report and subsequent decision-making. Some participants played a pricing game and lost by a narrow or wide margin, while others were asked to imagine losing by such margins. Participants who experienced a narrow loss reported more regret than those who imagined a narrow loss. Furthermore, those experiencing a narrow loss behaved more cautiously in a subsequent gambling task. Thus, the study provides self-report and behavioral evidence for a reversal of the affective forecasting phenomenon for feelings of regret.

Association of sleep and fatigue with decision regret among critical care nurses.

Science.gov (United States)

Scott, Linda D; Arslanian-Engoren, Cynthia; Engoren, Milo C

2014-01-01

The effects of inadequate sleep on clinical decisions may be important for patients in critical care units, who are often more vulnerable than patients in other units. Fatigued nurses are more likely than well-rested nurses to make faulty decisions that lead to decision regret, a negative cognitive emotion that occurs when the actual outcome differs from the desired or expected outcome. To examine the association between selected sleep variables, impairment due to fatigue, and clinical-decision self-efficacy and regret among critical care nurses. Decision regret was the primary outcome variable. Methods A nonexperimental, descriptive design and extant measures were used to obtain data from a random sample of full-time nurses. Binary logistic regression models were used to examine the association between sleep variables, fatigue, and clinical-decision self-efficacy and regret. The discrimination of the models was compared with the C statistic, the area under the receiver operating characteristic curve. A total of 605 nurses returned the questionnaires (17% response rate). Among these, decision regret was reported by 157 of 546 (29%). Nurses with decision regret reported more fatigue, more daytime sleepiness, less intershift recovery, and worse sleep quality than did nurses without decision regret. Being male, working a 12-hour shift, and clinical-decision satisfaction were significantly associated with decision regret (C statistic, 0.719; SE, 0.024). Nurses who experience impairments due to fatigue, loss of sleep, and inability to recover between shifts are more likely than unimpaired nurses to report decision regret.

The role of interpersonal harm in distinguishing regret from guilt.

Science.gov (United States)

Zeelenberg, Marcel; Breugelmans, Seger M

2008-10-01

Regret and guilt are emotions that are produced by negative outcomes for which one is responsible. Both emotions have received ample attention in the psychological literature; however, it is still unclear to what extent regret and guilt represent distinct psychological processes. We examined the extent to which the distinction between interpersonal harm (negative outcomes for others) and intrapersonal harm (negative outcomes for self) is crucial in differentiating these two emotions. In a series of 3 studies we found that guilt is predominantly felt in situations of interpersonal harm, whereas regret is felt in both situations of interpersonal harm and intrapersonal harm. Moreover, the results show that in situations of interpersonal harm the phenomenology of regret shares many, but not all features with the phenomenology of guilt. We conclude that the emotion processes resulting from interpersonal and intrapersonal harm are clearly distinct, but that regret as an emotion label is applied to both types of processes whereas the emotion label guilt is primarily used to refer to experiences of interpersonal harm. Implications for emotion research are discussed. (c) 2008 APA, all rights reserved

Regret causes ego-depletion and finding benefits in the regrettable events alleviates ego-depletion.

Science.gov (United States)

Gao, Hongmei; Zhang, Yan; Wang, Fang; Xu, Yan; Hong, Ying-Yi; Jiang, Jiang

2014-01-01

This study tested the hypotheses that experiencing regret would result in ego-depletion, while finding benefits (i.e., "silver linings") in the regret-eliciting events counteracted the ego-depletion effect. Using a modified gambling paradigm (Experiments 1, 2, and 4) and a retrospective method (Experiments 3 and 5), five experiments were conducted to induce regret. Results revealed that experiencing regret undermined performance on subsequent tasks, including a paper-and-pencil calculation task (Experiment 1), a Stroop task (Experiment 2), and a mental arithmetic task (Experiment 3). Furthermore, finding benefits in the regret-eliciting events improved subsequent performance (Experiments 4 and 5), and this improvement was mediated by participants' perceived vitality (Experiment 4). This study extended the depletion model of self-regulation by considering emotions with self-conscious components (in our case, regret). Moreover, it provided a comprehensive understanding of how people felt and performed after experiencing regret and after finding benefits in the events that caused the regret.

Regulatory Mode and Risk-Taking: The Mediating Role of Anticipated Regret.

Science.gov (United States)

Panno, Angelo; Lauriola, Marco; Pierro, Antonio

2015-01-01

We propose that decision maker's regulatory mode affects risk-taking through anticipated regret. In the Study 1 either a locomotion or an assessment orientation were experimentally induced, and in the Studies 2 and 3 these different orientations were assessed as chronic individual differences. To assess risk-taking we used two behavioral measures of risk: BART and hot-CCT. The results show that experimentally induced assessment orientation--compared to locomotion--leads to decreased risk-taking through increased anticipated regret (Study 1). People chronically predisposed to be in the assessment state take less risk through increased anticipated regret (Study 2 and Study 3). Study 2 results also show a marginally non-significant indirect effect of chronic locomotion mode on BART through anticipated regret. Differently, Study 3 shows that people chronically predisposed to be in the locomotion state take greater risk through decreased anticipated regret, when play a dynamic risk task triggering stronger emotional arousal. Through all three studies, the average effect size for the relationship of assessment with anticipated regret was in the moderate-large range, whereas for risk-taking was in the moderate range. The average effect size for the relationship of locomotion with anticipated regret was in the moderate range, whereas for risk-taking was in the small-moderate range. These results increase our understanding of human behavior under conditions of risk obtaining novel insights into regulatory mode theory and decision science.

Every third Kazakhstani medical student regrets the choice of ...

African Journals Online (AJOL)

Background: Many physicians regret about their choice of profession. However, no studies on this topic have been performed in Central Asia. Objective: To assess the proportion of medical students who regret their choice of education and to study factors associated with this outcome in Kazakhstan. Methods: This is a ...

The effects of anticipated regret on risk preferences of social and problem gamblers

Directory of Open Access Journals (Sweden)

Karin Tochkov

2009-04-01

Full Text Available Anticipated regret is an important determinant in risky decision making, however only a few studies have explored its role in problem gambling. This study tested for differences in the anticipation of regret among social and problem gamblers and examined how these differences affect risk preferences in a gambling task. The extent of problem gambling was assessed using the South Oaks Gambling Screen and participants were randomly assigned to one of two conditions. In the risky feedback condition, the feeling of regret was avoided by choosing the risky gamble, whereas in the safe feedback condition the safe gamble was the regret-minimizing option. Problem gambling was associated with the choice of the risky gamble in both conditions indicating less sensitivity to anticipated regret. It was also associated with risk seeking across feedback conditions when the stakes of winning and loosing were higher. These findings suggest that less regret or the poor anticipation of regret might contribute to excessive gambling and thus need to be addressed in cognitive treatments of problem gambling.

Regret and Responsibility Resolved? Evaluation Ordonez and Connolly's Conclusions.

NARCIS (Netherlands)

Zeelenberg, M.; van Dijk, W.W.; Manstead, A.S.R.

2000-01-01

T. Connolly, L. D. Ordo;aan;atez, and R. Coughlan (1997, Organizational Behavior and Human Decision Processes, 70, 73-85) argued, on the basis of 5 experiments, that regret need not be related to a sense of responsibility for the regretted outcome. We (M. Zeelenberg, W. W. van Dijk, & A. S. R.

Are K-12 Learners Motivated in Physical Education? A Meta-Analysis

Science.gov (United States)

Chen, Senlin; Chen, Ang; Zhu, Xihe

2012-01-01

Previous studies devoted to K-12 learner motivation in physical education share a general assumption that students may lack motivation. This meta-analytic study examined published original studies (n = 79) to determine students' motivation level and the association between motivation and outcomes. Original means of motivation measures were…

Accounting for perception in random regret choice models: Weberian and generalized Weberian specifications

NARCIS (Netherlands)

Jang, S.; Rasouli, S.; Timmermans, H.J.P.

2016-01-01

Recently, regret-based choice models have been introduced in the travel behavior research community as an alternative to expected/random utility models. The fundamental proposition underlying regret theory is that individuals minimize the amount of regret they (are expected to) experience when

Examining Trust, Forgiveness and Regret as Computational Concepts

Science.gov (United States)

Marsh, Stephen; Briggs, Pamela

The study of trust has advanced tremendously in recent years, to the extent that the goal of a more unified formalisation of the concept is becoming feasible. To that end, we have begun to examine the closely related concepts of regret and forgiveness and their relationship to trust and its siblings. The resultant formalisation allows computational tractability in, for instance, artificial agents. Moreover, regret and forgiveness, when allied to trust, are very powerful tools in the Ambient Intelligence (AmI) security area, especially where Human Computer Interaction and concrete human understanding are key. This paper introduces the concepts of regret and forgiveness, exploring them from social psychological as well as a computational viewpoint, and presents an extension to Marsh's original trust formalisation that takes them into account. It discusses and explores work in the AmI environment, and further potential applications.

Clinical decision regret among critical care nurses: a qualitative analysis.

Science.gov (United States)

Arslanian-Engoren, Cynthia; Scott, Linda D

2014-01-01

Decision regret is a negative cognitive emotion associated with experiences of guilt and situations of interpersonal harm. These negative affective responses may contribute to emotional exhaustion in critical care nurses (CCNs), increased staff turnover rates and high medication error rates. Yet, little is known about clinical decision regret among CCNs or the conditions or situations (e.g., feeling sleepy) that may precipitate its occurrence. To examine decision regret among CCNs, with an emphasis on clinical decisions made when nurses were most sleepy. A content analytic approach was used to examine the narrative descriptions of clinical decisions by CCNs when sleepy. Six decision regret themes emerged that represented deviations in practice or performance behaviors that were attributed to fatigued CCNs. While 157 CCNs disclosed a clinical decision they made at work while sleepy, the prevalence may be underestimated and warrants further investigation. Copyright © 2014 Elsevier Inc. All rights reserved.

Fear appeals in HIV prevention: the role of anticipated regret.

Science.gov (United States)

Smerecnik, Chris M R; Ruiter, Robert A C

2010-10-01

The present study examined the role of a number of cognitive beliefs (i.e. attitude, subjective norm, anticipated regret, and self-efficacy) in explaining the effects of fear appeal information on behavioral motivation. A randomized experiment with a 2 (threat: low versus high) × 2 (coping: low versus high) between-subjects design was used in the study. Undergraduates were exposed to one of four scenario messages that presented high or low threat information about HIV/AIDS combined with high or low coping information with regard to condom use in HIV prevention. Explorative analyses revealed that only anticipated regret qualified as a mediator of the effect of the fear appeal message on intention. High coping information was observed to increase anticipated regret, which increased the intention to use condoms. Anticipated regret mediated the coping-intention relationship. This finding furthers our understanding of the working mechanisms of fear appeals in HIV prevention.

Battling Obesity in K-12 Learners from an Exercise Physiology Perspective

Science.gov (United States)

Rattigan, Peter; Biren, Greg

2007-01-01

Physical education practitioners and programs have the opportunity and obligation to help children become physically educated, healthy, and active adults. This article discusses the battle against obesity in K-12 learners from an exercise physiology perspective and focuses on the fact that practitioners have all the tools they need to battle this…

Spirituality is associated with less treatment regret in men with localized prostate cancer.

Science.gov (United States)

Mollica, Michelle A; Underwood, Willie; Homish, Gregory G; Homish, D Lynn; Orom, Heather

2017-11-01

Some patients with prostate cancer regret their treatment choice. Treatment regret is associated with lower physical and mental quality of life. We investigated whether, in men with prostate cancer, spirituality is associated with lower decisional regret 6 months after treatment and whether this is, in part, because men with stronger spiritual beliefs experience lower decisional conflict when they are deciding how to treat their cancer. One thousand ninety three patients with prostate cancer (84% white, 10% black, and 6% Hispanic; mean age = 63.18; SD = 7.75) completed measures of spiritual beliefs and decisional conflict after diagnosis and decisional regret 6 months after treatment. We used multivariable linear regression to test whether there is an association between spirituality and decisional regret and structural equation modeling to test whether decisional conflict mediated this relationship. Stronger spiritual beliefs were associated with less decisional regret (b = -0.39, 95% CI = -0.53, -0.26, P conflict partially (38%) mediated the effect of spirituality on regret (indirect effect: b = -0.16, 95% CI = -0.21, -0.12, P Spirituality may help men feel less conflicted about their cancer treatment decisions and ultimately experience less decisional regret. Psychosocial support post-diagnosis could include clarification of spiritual values and opportunities to reappraise the treatment decision-making challenge in light of these beliefs. Copyright © 2016 John Wiley & Sons, Ltd.

Trust me (or not) : Regret and disappointment in experimental economic games

NARCIS (Netherlands)

Martinez, L.F.; Zeelenberg, Marcel

2015-01-01

Emotional states exert an influence on trust and the reciprocation of trust. The current research found that regret and disappointment, though both negatively valenced, have distinct effects on trust (and trustworthiness). Three experiments showed that regret decreased trust and trustworthiness,

Long-term decision regret after post-prostatectomy image-guided intensity-modulated radiotherapy.

Science.gov (United States)

Shakespeare, Thomas P; Chin, Stephen; Manuel, Lucy; Wen, Shelly; Hoffman, Matthew; Wilcox, Shea W; Aherne, Noel J

2017-02-01

Decision regret (DR) may occur when a patient believes their outcome would have been better if they had decided differently about their management. Although some studies investigate DR after treatment for localised prostate cancer, none report DR in patients undergoing surgery and post-prostatectomy radiotherapy. We evaluated DR in this group of patients overall, and for specific components of therapy. We surveyed 83 patients, with minimum 5 years follow-up, treated with radical prostatectomy (RP) and post-prostatectomy image-guided intensity-modulated radiotherapy (IG-IMRT) to 64-66 Gy following www.EviQ.org.au protocols. A validated questionnaire identified DR if men either indicated that they would have been better off had they chosen another treatment, or they wished they could change their mind about treatment. There was an 85.5% response rate, with median follow-up post-IMRT 78 months. Adjuvant IG-IMRT was used in 28% of patients, salvage in 72% and ADT in 48%. A total of 70% of patients remained disease-free. Overall, 16.9% of patients expressed DR for treatment, with fourfold more regret for the RP component of treatment compared to radiotherapy (16.9% vs 4.2%, P = 0.01). DR for androgen deprivation was 14.3%. Patients were regretful of surgery due to toxicity, not being adequately informed about radiotherapy as an alternative, positive margins and surgery costs (83%, 33%, 25% and 8% of regretful patients respectively). Toxicity caused DR in the three radiotherapy-regretful and four ADT-regretful patients. Patients were twice as regretful overall, and of surgery, for salvage vs adjuvant approaches (both 19.6% vs 10.0%). Decision regret after RP and post-prostatectomy IG-IMRT is uncommon, although patients regret RP more than post-operative IG-IMRT. This should reassure urologists referring patients for post-prostatectomy IG-IMRT, particularly in the immediate adjuvant setting. Other implications include appropriate patient selection for RP (and

Evaluation of Influencing Factors on Tubal Sterilization Regret: A Cross-Sectional Study

Directory of Open Access Journals (Sweden)

Shahideh Jahanian Sadatmahalleh

2018-06-01

Full Text Available Background The aim of this study is to evaluate the menstrual pattern, sexual function, and anxiety, and depression in women with poststerilization regret, and potential influencing factors for regret following tubal ligation (TL in Iranian women. Materials and Methods In this cross-sectional study, 166 women with TL were subdivided into two groups including women with poststerilization regret (n=41 and women without poststerilization regret (n=125. They were selected from a health care center in Guilan province (Iran during 2015-2016. Menstrual blood loss was measured using the Pictorial Blood Loss Assessment Chart (PBLAC and through a self-administered questionnaire. In addition, sexual function was assessed by the Female Sexual Function Index (FSFI, and psychological distress was measured by employing the Hospital Anxiety and Depression Scale (HADS. Student’s t test and Chi-square test were used to reveal the statistical differences between the two groups. We used logistic regression to determine the influencing factors associated with regretting sterilization. Results Women with poststerilization regret had more menorrhagia (78 vs. 57.6%, P=0.03 than those who did not regret sterilization. A significant difference was found in sexual dysfunction in orgasm (P=0.02, satisfaction (P=0.004, pain (P=0.02, and total FSFI scores (P=0.007 between the two groups. Also, there was a significant difference between the two groups in anxiety, depression and total scores HADS (P=0.01. In the logistic regression model, age of sterilization [odds ratio (OR=2.67, confidence interval (CI: 1.03-7.81, P=0.04], pre-sterilization counseling (OR=19.92, CI: 6.61-59.99, P<0.001, score of PBLAC (OR=1.01, CI: 1.004-1.01, P=0.001, the number of days of bleeding (OR=1.37, CI: 1.01-1.99, P=0.04, and the length of menstrual cycles (OR=0.91, CI: 0.84-0.99, P=0.03 were significantly associated with regretting sterilization. Conclusion Complications due to sterilization are

The regrets of procrastination in climate policy

Energy Technology Data Exchange (ETDEWEB)

Keller, Klaus [Department of Geosciences, Penn State, University Park, PA 16802 (United States); Robinson, Alexander [Department of Geosciences, Penn State, University Park, PA 16802 (United States); Bradford, David F [Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ 08540 (United States); Oppenheimer, Michael [Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ 08540 (United States)

2007-04-01

Anthropogenic carbon dioxide (CO{sub 2}) emissions are projected to impose economic costs due to the associated climate change impacts. Climate change impacts can be reduced by abating CO{sub 2} emissions. What would be an economically optimal investment in abating CO{sub 2} emissions? Economic models typically suggest that reducing CO{sub 2} emissions by roughly ten to twenty per cent relative to business-as-usual would be an economically optimal strategy. The currently implemented CO{sub 2} abatement of a few per cent falls short of this benchmark. Hence, the global community may be procrastinating in implementing an economically optimal strategy. Here we use a simple economic model to estimate the regrets of this procrastination-the economic costs due to the suboptimal strategy choice. The regrets of procrastination can range from billions to trillions of US dollars. The regrets increase with increasing procrastination period and with decreasing limits on global mean temperature increase. Extended procrastination may close the window of opportunity to avoid crossing temperature limits interpreted by some as 'dangerous anthropogenic interference with the climate system' in the sense of Article 2 of the United Nations Framework Convention on Global Climate Change.

The regrets of procrastination in climate policy

Energy Technology Data Exchange (ETDEWEB)

Keller, Klaus [Department of Geosciences, Penn State, University Park, PA 16802 (United States); Robinson, Alexander [Department of Geosciences, Penn State, University Park, PA 16802 (United States); Bradford, David F [Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ 08540 (United States); Oppenheimer, Michael [Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ 08540 (United States)

2007-04-01

Anthropogenic carbon dioxide (CO{sub 2}) emissions are projected to impose economic costs due to the associated climate change impacts. Climate change impacts can be reduced by abating CO{sub 2} emissions. What would be an economically optimal investment in abating CO{sub 2} emissions? Economic models typically suggest that reducing CO{sub 2} emissions by roughly ten to twenty per cent relative to business-as-usual would be an economically optimal strategy. The currently implemented CO{sub 2} abatement of a few per cent falls short of this benchmark. Hence, the global community may be procrastinating in implementing an economically optimal strategy. Here we use a simple economic model to estimate the regrets of this procrastination-the economic costs due to the suboptimal strategy choice. The regrets of procrastination can range from billions to trillions of US dollars. The regrets increase with increasing procrastination period and with decreasing limits on global mean temperature increase. Extended procrastination may close the window of opportunity to avoid crossing temperature limits interpreted by some as 'dangerous anthropogenic interference with the climate system' in the sense of Article 2 of the United Nations Framework Convention on Global Climate Change.

The regrets of procrastination in climate policy

Science.gov (United States)

Keller, Klaus; Robinson, Alexander; Bradford, David F.; Oppenheimer, Michael

2007-04-01

Anthropogenic carbon dioxide (CO2) emissions are projected to impose economic costs due to the associated climate change impacts. Climate change impacts can be reduced by abating CO2 emissions. What would be an economically optimal investment in abating CO2 emissions? Economic models typically suggest that reducing CO2 emissions by roughly ten to twenty per cent relative to business-as-usual would be an economically optimal strategy. The currently implemented CO2 abatement of a few per cent falls short of this benchmark. Hence, the global community may be procrastinating in implementing an economically optimal strategy. Here we use a simple economic model to estimate the regrets of this procrastination—the economic costs due to the suboptimal strategy choice. The regrets of procrastination can range from billions to trillions of US dollars. The regrets increase with increasing procrastination period and with decreasing limits on global mean temperature increase. Extended procrastination may close the window of opportunity to avoid crossing temperature limits interpreted by some as 'dangerous anthropogenic interference with the climate system' in the sense of Article 2 of the United Nations Framework Convention on Global Climate Change.

The regrets of procrastination in climate policy

International Nuclear Information System (INIS)

Keller, Klaus; Robinson, Alexander; Bradford, David F; Oppenheimer, Michael

2007-01-01

Anthropogenic carbon dioxide (CO 2 ) emissions are projected to impose economic costs due to the associated climate change impacts. Climate change impacts can be reduced by abating CO 2 emissions. What would be an economically optimal investment in abating CO 2 emissions? Economic models typically suggest that reducing CO 2 emissions by roughly ten to twenty per cent relative to business-as-usual would be an economically optimal strategy. The currently implemented CO 2 abatement of a few per cent falls short of this benchmark. Hence, the global community may be procrastinating in implementing an economically optimal strategy. Here we use a simple economic model to estimate the regrets of this procrastination-the economic costs due to the suboptimal strategy choice. The regrets of procrastination can range from billions to trillions of US dollars. The regrets increase with increasing procrastination period and with decreasing limits on global mean temperature increase. Extended procrastination may close the window of opportunity to avoid crossing temperature limits interpreted by some as 'dangerous anthropogenic interference with the climate system' in the sense of Article 2 of the United Nations Framework Convention on Global Climate Change

Comparing the experience of regret and its predictors among smokers in four Asian countries: findings from the ITC surveys in Thailand, South Korea, Malaysia, and China.

Science.gov (United States)

Sansone, Natalie; Fong, Geoffrey T; Lee, Wonkyong B; Laux, Fritz L; Sirirassamee, Buppha; Seo, Hong-Gwan; Omar, Maizurah; Jiang, Yuan

2013-10-01

Nearly all smokers in high-income Western countries report that they regret smoking (Fong, G. T., Hammond, D., Laux, F. L., Zanna, M. P., Cummings, M. K., Borland, R., & Ross, H. [2004]. The near-universal experience of regret among smokers in four countries: Findings from the International Tobacco Control Policy Evaluation Survey. Nicotine and Tobacco Research, 6, S341-S351. doi:10.1080/14622200412331320743), but no research to date has examined the prevalence of regret among smokers in non-Western, low- and middle-income countries. Data were from the International Tobacco Control (ITC) Surveys of smokers in 4 Asian countries (China, Malaysia, South Korea, and Thailand); N = 9,738. Regret was measured with the statement: "If you had to do it over again, you would not have started smoking." Prevalence of regret in 3 countries (South Korea = 87%, Malaysia = 77%, and China = 74%) was lower than that found by Fong et al. in the United States, Australia, Canada, and the United Kingdom (89%-90%); but was higher in Thailand (93%). These significant country differences in regret corresponded with differences in tobacco control and norms regarding smoking. The predictors of regret in the Asian countries were very similar to those in the 4 Western countries: Regret was more likely to be experienced by smokers who smoked fewer cigarettes per day, perceived greater benefits of quitting and higher financial costs of smoking, had more prior quit attempts, worried that smoking would damage their health, and felt that their loved ones and society disapproved of smoking. Regret was also positively associated with intentions to quit (r = 0.23, p tobacco control and is related to factors associated with future quitting.

Behavioural consequences of regret and disappointment in social bargaining games.

Science.gov (United States)

Martinez, Luis M F; Zeelenberg, Marcel; Rijsman, John B

2011-02-01

Previous research on the role of negative emotions in social bargaining games has focused primarily on social emotions such as anger and guilt. In this article, we provide a test for behavioural differences between two prototypical decision-related negative emotions-regret and disappointment-in one-shot social dilemma games. Three experiments with two different emotion-induction procedures (autobiographical recall and imagined scenarios) and two different games (the ultimatum game and the 10-coin give-some game) revealed that regret increased prosocial behaviour, whereas disappointment decreased prosocial behaviour. These results extend previous findings concerning differences between regret and disappointment to interdependent (social) situations. © 2010 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

The Development of Regret

Science.gov (United States)

O'Connor, Eimear; McCormack, Teresa; Feeney, Aidan

2012-01-01

In two experiments, 4- to 9-year-olds played a game in which they selected one of two boxes to win a prize. On "regret" trials the unchosen box contained a better prize than the prize children actually won, and on "baseline" trials the other box contained a prize of the same value. Children rated their feelings about their prize before and after…

Waves of regret: A MEG study of emotion and decision-making

NARCIS (Netherlands)

Giorgetta, C.; Grecucci, A.; Bonini, N.; Coricelli, G.; Demarchi, G.; Braun, C.; Sanfey, A.G.

2013-01-01

Recent fMRI studies have investigated brain activity involved in the feeling of regret and disappointment by manipulating the feedback participants saw after making a decision to play certain gambles: full-feedback (regret: participant sees the outcomes from both the chosen and unchosen gamble) vs.

Markov Chains and Markov Processes

OpenAIRE

Ogunbayo, Segun

2016-01-01

Markov chain, which was named after Andrew Markov is a mathematical system that transfers a state to another state. Many real world systems contain uncertainty. This study helps us to understand the basic idea of a Markov chain and how is been useful in our daily lives. For some times there had been suspense on distinct predictions and future existences. Also in different games there had been different expectations or results involved. That is the reason why we need Markov chains to predict o...

Regret Expression and Social Learning Increases Delay to Sexual Gratification.

Directory of Open Access Journals (Sweden)

Amanda J Quisenberry

Full Text Available Modification and prevention of risky sexual behavior is important to individuals' health and public health policy. This study employed a novel sexual discounting task to elucidate the effects of social learning and regret expression on delay to sexual gratification in a behavioral task.Amazon Mechanical Turk Workers were assigned to hear one of three scenarios about a friend who engages in similar sexual behavior. The scenarios included a positive health consequence, a negative health consequence or a negative health consequence with the expression of regret. After reading one scenario, participants were asked to select from 60 images, those with whom they would have casual sex. Of the selected images, participants chose one image each for the person they most and least want to have sex with and person most and least likely to have a sexually transmitted infection. They then answered questions about engaging in unprotected sex now or waiting some delay for condom-protected sex in each partner condition.Results indicate that the negative health outcome scenario with regret expression resulted in delayed sexual gratification in the most attractive and least STI partner conditions, whereas in the least attractive and most STI partner conditions the negative health outcome with and without regret resulted in delayed sexual gratification.Results suggest that the sexual discounting task is a relevant laboratory measure and the framing of information to include regret expression may be relevant for prevention of risky sexual behavior.

Markov processes and controlled Markov chains

CERN Document Server

Filar, Jerzy; Chen, Anyue

2002-01-01

The general theory of stochastic processes and the more specialized theory of Markov processes evolved enormously in the second half of the last century. In parallel, the theory of controlled Markov chains (or Markov decision processes) was being pioneered by control engineers and operations researchers. Researchers in Markov processes and controlled Markov chains have been, for a long time, aware of the synergies between these two subject areas. However, this may be the first volume dedicated to highlighting these synergies and, almost certainly, it is the first volume that emphasizes the contributions of the vibrant and growing Chinese school of probability. The chapters that appear in this book reflect both the maturity and the vitality of modern day Markov processes and controlled Markov chains. They also will provide an opportunity to trace the connections that have emerged between the work done by members of the Chinese school of probability and the work done by the European, US, Central and South Ameri...

Expanding the applicability of random regret minimization for route choice analysis

DEFF Research Database (Denmark)

Prato, Carlo Giacomo

2014-01-01

The discrete choice paradigm of random regret minimization (RRM) has been recently proposed in several choice contexts. In the route choice context, the paradigm has been used to model the choice among three routes and to formulate regret-based stochastic user equilibrium. However, in the same co...

Timing matters: length of leave and working mothers' daily reentry regrets.

Science.gov (United States)

Wiese, Bettina S; Ritter, Johannes O

2012-11-01

Dealing with developmental tasks in work and family domains is an important challenge for young and middle-aged adults. We investigated a transition that has evolved into a normative task for women, namely, the retransition back to paid work following maternity leave. In a diary study with 149 mothers who had just returned to work, we examined the daily experienced regrets concerning this return. In addition to personal resources (i.e., emotional stability, feeling prepared for the transition) and financial requirements needed to return to work, daily experienced family stress predicted decisional regrets. Moreover, our results suggest that leave length is related to psychological resilience in the face of day-to-day stress experiences: Late returners reported fewer regrets in general and were unaffected by daily family stress. Return-to-work regrets, in turn, were predictive of withdrawal intentions. This underlines the relevancy of the timing of the transition back to work in terms of successful development during this life phase.

Brain, emotion and decision making: the paradigmatic example of regret.

Science.gov (United States)

Coricelli, Giorgio; Dolan, Raymond J; Sirigu, Angela

2007-06-01

Human decisions cannot be explained solely by rational imperatives but are strongly influenced by emotion. Theoretical and behavioral studies provide a sound empirical basis to the impact of the emotion of regret in guiding choice behavior. Recent neuropsychological and neuroimaging data have stressed the fundamental role of the orbitofrontal cortex in mediating the experience of regret. Functional magnetic resonance imaging data indicate that reactivation of activity within the orbitofrontal cortex and amygdala occurring during the phase of choice, when the brain is anticipating possible future consequences of decisions, characterizes the anticipation of regret. In turn, these patterns reflect learning based on cumulative emotional experience. Moreover, affective consequences can induce specific mechanisms of cognitive control of the choice processes, involving reinforcement or avoidance of the experienced behavior.

The Influence of Counterfactual Thinking and Regret on Ethical Decision Making

Science.gov (United States)

Celuch, Kevin; Saxby, Carl; Oeding, Jill

2015-01-01

The authors explore the influence of counterfactual thoughts in triggering the emotions of regret and disappointment in ethical decision making. Counterfactual thinking involves examining possible outcomes to events and is often explored in what-if scenarios. Findings support that subjects were able to transfer regret (but not disappointment)…

Risk Route Choice Analysis and the Equilibrium Model under Anticipated Regret Theory

Directory of Open Access Journals (Sweden)

pengcheng yuan

2014-02-01

Full Text Available The assumption about travellers’ route choice behaviour has major influence on the traffic flow equilibrium analysis. Previous studies about the travellers’ route choice were mainly based on the expected utility maximization theory. However, with the gradually increasing knowledge about the uncertainty of the transportation system, the researchers have realized that there is much constraint in expected util­ity maximization theory, because expected utility maximiza­tion requires travellers to be ‘absolutely rational’; but in fact, travellers are not truly ‘absolutely rational’. The anticipated regret theory proposes an alternative framework to the tra­ditional risk-taking in route choice behaviour which might be more scientific and reasonable. We have applied the antici­pated regret theory to the analysis of the risk route choosing process, and constructed an anticipated regret utility func­tion. By a simple case which includes two parallel routes, the route choosing results influenced by the risk aversion degree, regret degree and the environment risk degree have been analyzed. Moreover, the user equilibrium model based on the anticipated regret theory has been established. The equivalence and the uniqueness of the model are proved; an efficacious algorithm is also proposed to solve the model. Both the model and the algorithm are demonstrated in a real network. By an experiment, the model results and the real data have been compared. It was found that the model re­sults can be similar to the real data if a proper regret degree parameter is selected. This illustrates that the model can better explain the risk route choosing behaviour. Moreover, it was also found that the traveller’ regret degree increases when the environment becomes more and more risky.

Eliciting regret improves decision making at the end of life.

Science.gov (United States)

Djulbegovic, Benjamin; Tsalatsanis, Athanasios; Mhaskar, Rahul; Hozo, Iztok; Miladinovic, Branko; Tuch, Howard

2016-11-01

Management choices at the end of life are high-stake decisions fraught with emotions, chief among is regret. Our objective in this paper is to test the utility of a regret-based model to facilitate referral to hospice care while helping patients clarify their preferences on how they wish to spend the remaining days of their lives. A prospective cohort study that enrolled consecutive adult patients (n = 178) aware of the terminal nature of their disease. The patients were at the point in care where they had to decide between continuing potentially 'curative/life-prolonging' treatment (Rx) versus hospice care. Preferences were elicited using a Dual Visual Analog Scale regarding the level of regret of omission versus commission (RgO/RgC) towards hospice care and Rx. Each patient's RgO/RgC was contrasted against the predictive probability of death to suggest a management plan, which was then compared with the patient's actual choice. The probability of death was estimated using validated Palliative Performance Scale predictive model. Eighty-five percent (151/178) of patients agreed with the model's recommendations (p < 0.000001). Model predicted the actual choices for 72% (128/178) of patients (p < 0.00001). Logistic regression analysis showed that people who were initially inclined to be referred to hospice and were predicted to choose hospice over disease-directed treatment by the regret model have close to 98% probability of choosing hospice care at the end of their lives. No other factors (age, gender, race, educational status and pain level) affected their choice. Using regret to elicit choices in the end-of-life setting is both descriptively and prescriptively valid. People with terminal disease who are initially inclined to choose hospice and do not regret such a choice will select hospice care with high level of certainty. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Consequences of regret aversion : effects of expected feedback on risky decision making

NARCIS (Netherlands)

Zeelenberg, M.; Beattie, J.; Pligt, van der J.; Vries, de N.K.

1996-01-01

Previous research has considered the question of how anticipated regret affects risky decision making. Several studies have shown that anticipated regret forces participants towards the safe option, showing risk-aversion. We argue that these results are due to the previous confounding of the

Feelings of regret and disappointment in adults with high-functioning autism.

Science.gov (United States)

Zalla, Tiziana; Sirigu, Angela; Robic, Suzanne; Chaste, Pauline; Leboyer, Marion; Coricelli, Giorgio

2014-09-01

Impairments in emotional processing in Autism Spectrum Disorders (ASDs) can be characterised by failure to generate and recognize self-reflective, cognitive-based emotions, such as pride, embarrassment and shame. Among this type of emotions, regret and disappointment, as well as their positive counterparts, result from a counterfactual comparison, that is the comparison between an actual value ("what is") and a fictive value ("what might have been"). However, while disappointment is experienced when the obtained outcome is worse than the expected outcome that might have occurred from the same choice, regret occurs when one experiences an outcome that is worse than the outcome of foregone choices. By manipulating a simple gambling task, we examined subjective reports on the intensity of negative and positive emotions in a group of adults with High-Functioning Autism or Asperger syndrome (HFA/AS), and a control group matched for age, gender and educational level. Participants were asked to choose between two lotteries with different levels of risk under two conditions of outcome feedback: (i) Partial, in which only the outcome of the chosen lottery was visible, (ii) Complete, in which the outcomes of the two lotteries were simultaneously visible. By comparing partial and complete conditions, we aimed to investigate the differential effect between disappointment and regret, as well as between their positive counterparts. Relative to the control participants (CP), the group with HFA/AS reported reduced regret and no difference between regret and disappointment, along with a preserved ability to use counterfactual thinking and similar choice behaviour. Difficulties to distinguish the feeling of regret in participants with HFA/AS can be explained by diminished emotional awareness, likely associated with an abnormal fronto-limbic connectivity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Parental Decisional Regret after Primary Distal Hypospadias Repair: Family and Surgery Variables, and Repair Outcomes.

Science.gov (United States)

Ghidini, Filippo; Sekulovic, Sasa; Castagnetti, Marco

2016-03-01

Decisional regret is defined as distress after making a health care choice and can be an issue for parents electing distal hypospadias repair for their sons. We assessed the influence on decisional regret of variables related to the family, surgery and outcomes. Charts for 372 patients undergoing primary distal hypospadias repair between 2005 and 2012 were reviewed, and validated questionnaires, including the Decisional Regret Scale, Pediatric Penile Perception Score and Dysfunctional Voiding and Incontinence Scoring System, were administered to parents. Data were available for 172 of 372 families (response rate 46.2%). Of 323 parents 128 (39.6%) presented with moderately strong decisional regret, with good agreement within couples. Predictors of decisional regret included intermediate parental educational level (OR 3.19, 95% CI 1.52-6.69), patient not being the first born (OR 2.01, 95% CI 1.07-3.78), family history of hypospadias (OR 4.42, 95% CI 1.96-9.97), initial desire to avoid surgery (OR 2.07, 95% CI 1.04-4.12), younger age at followup (OR 0.81, 95% CI 0.72-0.91), presence of lower urinary tract symptoms (OR 4.92, 95% CI 1.53-15.81) and lower Pediatric Penile Perception Score (OR 0.86, 95% CI 0.75-0.99). Decisional regret was unrelated to parental desire to avoid circumcision, surgical variables, development of complications and duration of followup. Decisional regret is a problem in a significant proportion of parents electing distal hypospadias repair for their sons. In our experience family variables seemed to be predictors of decisional regret, while surgical variables did not. Predictors of decisional regret included worse parental perception of penile appearance and the presence of lower urinary tract symptoms. However, the latter could be unrelated to surgery. Irrespective of the duration of followup, decisional regret seems decreased in parents of older patients. Copyright © 2016 American Urological Association Education and Research, Inc

Markov processes

CERN Document Server

Kirkwood, James R

2015-01-01

Review of ProbabilityShort HistoryReview of Basic Probability DefinitionsSome Common Probability DistributionsProperties of a Probability DistributionProperties of the Expected ValueExpected Value of a Random Variable with Common DistributionsGenerating FunctionsMoment Generating FunctionsExercisesDiscrete-Time, Finite-State Markov ChainsIntroductionNotationTransition MatricesDirected Graphs: Examples of Markov ChainsRandom Walk with Reflecting BoundariesGambler’s RuinEhrenfest ModelCentral Problem of Markov ChainsCondition to Ensure a Unique Equilibrium StateFinding the Equilibrium StateTransient and Recurrent StatesIndicator FunctionsPerron-Frobenius TheoremAbsorbing Markov ChainsMean First Passage TimeMean Recurrence Time and the Equilibrium StateFundamental Matrix for Regular Markov ChainsDividing a Markov Chain into Equivalence ClassesPeriodic Markov ChainsReducible Markov ChainsSummaryExercisesDiscrete-Time, Infinite-State Markov ChainsRenewal ProcessesDelayed Renewal ProcessesEquilibrium State f...

Regret and adaptive decision making in young children.

Science.gov (United States)

O'Connor, Eimear; McCormack, Teresa; Beck, Sarah R; Feeney, Aidan

2015-07-01

In line with the claim that regret plays a role in decision making, O'Connor, McCormack, and Feeney (Child Development, 85 (2014) 1995-2010) found that children who reported feeling sadder on discovering they had made a non-optimal choice were more likely to make a different choice the next time around. We examined two issues of interpretation regarding this finding: whether the emotion measured was indeed regret and whether it was the experience of this emotion, rather than the ability to anticipate it, that affected decision making. To address the first issue, we varied the degree to which children aged 6 or 7 years were responsible for an outcome, assuming that responsibility is a necessary condition for regret. The second issue was addressed by examining whether children could accurately anticipate that they would feel worse on discovering they had made a non-optimal choice. Children were more likely to feel sad if they were responsible for the outcome; however, even if they were not responsible, children were more likely than chance to report feeling sadder. Moreover, across all conditions, feeling sadder was associated with making a better subsequent choice. In a separate task, we demonstrated that children of this age cannot accurately anticipate feeling sadder on discovering that they had not made the best choice. These findings suggest that although children may feel regret following a non-optimal choice, even if they were not responsible for an outcome, they may experience another negative emotion such as frustration. Experiencing either of these emotions seems to be sufficient to support better decision making. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Effects of Pride and Regret on Geriatric Depression: A Cross-Cultural Study With Mixed-Methods Approaches.

Science.gov (United States)

Lee, Othelia E; Ryu, Seungah

2018-03-01

Pride and regret are self-conscious emotions that develop later in life and become a source of emotional struggle. This cross-cultural study examined the effect of the content and intensity of self-conscious emotions on Geriatric Depression Scale (GDS) scores. Among a convenience sample of 234 older adults (130 in the United States and 104 in South Korea), the contents and intensities of both life regrets and pride were examined. Although a greater variety of regrets was cited by Americans, overall Korean respondents reported higher intensity of regret. Regrets that were related to leisure and addiction among Americans and health and career among Koreans were predictors of the GDS scores. Pride in leisure activities for Americans and altruism among Koreans could alleviate depression. While regrets and pride explained a small amount of the variance in the GDS scores, current life stressors greatly contributed to geriatric depression.

Accelerating Literacy for Diverse Learners: Classroom Strategies That Integrate Social/Emotional Engagement and Academic Achievement, K-8. Second Edition

Science.gov (United States)

Herrera, Socorro G.; Kavimandan, Shabina K.; Perez, Della R.; Wessels, Stephanie

2017-01-01

Research indicates that the culturally responsive teaching strategies outlined in this book accelerate literacy, language development, and academic growth for students in grades K-8, particularly for English language learners. Completely revised and updated, this bestselling resource speaks to the social-emotional needs of learners and helps…

Psychopathic individuals exhibit but do not avoid regret during counterfactual decision making

Science.gov (United States)

Baskin-Sommers, Arielle; Stuppy-Sullivan, Allison M.; Buckholtz, Joshua W.

2016-01-01

Psychopathy is associated with persistent antisocial behavior and a striking lack of regret for the consequences of that behavior. Although explanatory models for psychopathy have largely focused on deficits in affective responsiveness, recent work indicates that aberrant value-based decision making may also play a role. On that basis, some have suggested that psychopathic individuals may be unable to effectively use prospective simulations to update action value estimates during cost–benefit decision making. However, the specific mechanisms linking valuation, affective deficits, and maladaptive decision making in psychopathy remain unclear. Using a counterfactual decision-making paradigm, we found that individuals who scored high on a measure of psychopathy were as or more likely than individuals low on psychopathy to report negative affect in response to regret-inducing counterfactual outcomes. However, despite exhibiting intact affective regret sensitivity, they did not use prospective regret signals to guide choice behavior. In turn, diminished behavioral regret sensitivity predicted a higher number of prior incarcerations, and moderated the relationship between psychopathy and incarceration history. These findings raise the possibility that maladaptive decision making in psychopathic individuals is not a consequence of their inability to generate or experience negative emotions. Rather, antisocial behavior in psychopathy may be driven by a deficit in the generation of forward models that integrate information about rules, costs, and goals with stimulus value representations to promote adaptive behavior. PMID:27911790

Psychopathic individuals exhibit but do not avoid regret during counterfactual decision making.

Science.gov (United States)

Baskin-Sommers, Arielle; Stuppy-Sullivan, Allison M; Buckholtz, Joshua W

2016-12-13

Psychopathy is associated with persistent antisocial behavior and a striking lack of regret for the consequences of that behavior. Although explanatory models for psychopathy have largely focused on deficits in affective responsiveness, recent work indicates that aberrant value-based decision making may also play a role. On that basis, some have suggested that psychopathic individuals may be unable to effectively use prospective simulations to update action value estimates during cost-benefit decision making. However, the specific mechanisms linking valuation, affective deficits, and maladaptive decision making in psychopathy remain unclear. Using a counterfactual decision-making paradigm, we found that individuals who scored high on a measure of psychopathy were as or more likely than individuals low on psychopathy to report negative affect in response to regret-inducing counterfactual outcomes. However, despite exhibiting intact affective regret sensitivity, they did not use prospective regret signals to guide choice behavior. In turn, diminished behavioral regret sensitivity predicted a higher number of prior incarcerations, and moderated the relationship between psychopathy and incarceration history. These findings raise the possibility that maladaptive decision making in psychopathic individuals is not a consequence of their inability to generate or experience negative emotions. Rather, antisocial behavior in psychopathy may be driven by a deficit in the generation of forward models that integrate information about rules, costs, and goals with stimulus value representations to promote adaptive behavior.

Cassandra's regret: The psychology of not wanting to know.

Science.gov (United States)

Gigerenzer, Gerd; Garcia-Retamero, Rocio

2017-03-01

Ignorance is generally pictured as an unwanted state of mind, and the act of willful ignorance may raise eyebrows. Yet people do not always want to know, demonstrating a lack of curiosity at odds with theories postulating a general need for certainty, ambiguity aversion, or the Bayesian principle of total evidence. We propose a regret theory of deliberate ignorance that covers both negative feelings that may arise from foreknowledge of negative events, such as death and divorce, and positive feelings of surprise and suspense that may arise from foreknowledge of positive events, such as knowing the sex of an unborn child. We conduct the first representative nationwide studies to estimate the prevalence and predictability of deliberate ignorance for a sample of 10 events. Its prevalence is high: Between 85% and 90% of people would not want to know about upcoming negative events, and 40% to 70% prefer to remain ignorant of positive events. Only 1% of participants consistently wanted to know. We also deduce and test several predictions from the regret theory: Individuals who prefer to remain ignorant are more risk averse and more frequently buy life and legal insurance. The theory also implies the time-to-event hypothesis, which states that for the regret-prone, deliberate ignorance is more likely the nearer the event approaches. We cross-validate these findings using 2 representative national quota samples in 2 European countries. In sum, we show that deliberate ignorance exists, is related to risk aversion, and can be explained as avoiding anticipatory regret. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The influence of anticipated regret on business start-up behaviour: A research note

NARCIS (Netherlands)

Hatak, Isabella; Snellman, Kirsi

This research note aims to develop the emotional underpinning of early-stage entrepreneurship by examining the influence of anticipated regret, a negative emotion, on the transformation of latent entrepreneurs into nascent entrepreneurs. Drawing on regret regulation theory and two waves of survey

Regret and Responsibility Resolved? Evaluating Ordóñez and Connolly's (2000) Conclusions.

Science.gov (United States)

Zeelenberg; van Dijk WW; Manstead

2000-01-01

T. Connolly, L. D. Ordo;aan;atez, and R. Coughlan (1997, Organizational Behavior and Human Decision Processes, 70, 73-85) argued, on the basis of 5 experiments, that regret need not be related to a sense of responsibility for the regretted outcome. We (M. Zeelenberg, W. W. van Dijk, & A. S. R. Manstead, 1998, Organizational Behavior and Human Decision Processes, 74, 254-272) showed in 2 experiments that this conclusion was premature, because it was based on an indirect measure of regret (i.e., overall happiness with the decision outcome). When regret was directly measured, the predicted effects of responsibility were found. L. D. Ordo;aan;atez and T. Connolly (2000, Organizational Behavior and Human Decision Processes, 81, 132-142) replicated our findings in 2 experiments. Based on their findings they arrived at 4 conclusions. In this rejoinder we first discuss Ordóñez and Connolly's new studies and we then discuss the validity of their 4 conclusions. Copyright 2000 Academic Press.

Consumer preferences for alternative fuel vehicles: Comparing a utility maximization and a regret minimization model

International Nuclear Information System (INIS)

Chorus, Caspar G.; Koetse, Mark J.; Hoen, Anco

2013-01-01

This paper presents a utility-based and a regret-based model of consumer preferences for alternative fuel vehicles, based on a large-scale stated choice-experiment held among company car leasers in The Netherlands. Estimation and application of random utility maximization and random regret minimization discrete choice models shows that while the two models achieve almost identical fit with the data and differ only marginally in terms of predictive ability, they generate rather different choice probability-simulations and policy implications. The most eye-catching difference between the two models is that the random regret minimization model accommodates a compromise-effect, as it assigns relatively high choice probabilities to alternative fuel vehicles that perform reasonably well on each dimension instead of having a strong performance on some dimensions and a poor performance on others. - Highlights: • Utility- and regret-based models of preferences for alternative fuel vehicles. • Estimation based on stated choice-experiment among Dutch company car leasers. • Models generate rather different choice probabilities and policy implications. • Regret-based model accommodates a compromise-effect

Evidence of depression-associated circadian rhythm disruption and regret in prostate cancer patients after surgery.

Science.gov (United States)

Christie, Joanne; Sharpley, Christopher F; Bitsika, Vicki; Christie, David

2017-12-01

The purpose of this study is to investigate the association between prostate cancer (PCa) patients' regret that their surgery harmed them, and their scores on the two key symptoms of major depressive disorder (depressed mood, anhedonia) and a symptom of melancholic depression (disruption to circadian rhythm). Forty PCa patients who had received surgery for their PCa completed a postal survey including background information, regret about surgery that 'did them a lot of harm' and three items drawn from the Zung Self-Rating Depression Scale measuring depressed mood, anhedonia and circadian rhythm disruption. There were significant correlations between all three symptoms of depression (depressed mood, anhedonia, disruption to circadian rhythm) and between patients' regret that surgery did them a lot of harm and their circadian rhythm disruption, but not between depressed mood or anhedonia and regret about surgery doing harm. These findings suggest that PCa patients' post-surgery regrets about major harm may lead to a significant disruption in a central physiological function and raise the need to consider this side effect of surgery when planning supportive services for these men.

RESTART simulation of non-Markov consecutive-k-out-of-n: F repairable systems

International Nuclear Information System (INIS)

Villen-Altamirano, Jose

2010-01-01

The reliability of consecutive-k-out-of-n: F repairable systems and (k-1)-step Markov dependence is studied. The model analyzed in this paper is more general than those of previous studies given that repair time and component lifetimes are random variables that follow a general distribution. The system has one repair service which adopts a priority repair rule based on system failure risk. Since crude simulation has proved to be inefficient for highly dependable systems, the RESTART method was used for the estimation of steady-state unavailability, MTBF and unreliability. Probabilities up to the order of 10 -16 have been accurately estimated with little computational effort. In this method, a number of simulation retrials are performed when the process enters regions of the state space where the chance of occurrence of a rare event (e.g., a system failure) is higher. The main difficulty for the application of this method is to find a suitable function, called the importance function, to define the regions. Given the simplicity involved in changing some model assumptions with RESTART, the importance function used in this paper could be useful for dependability estimation of many systems.

Random regret minimization : Exploration of a new choice model for environmental and resource economics

NARCIS (Netherlands)

Thiene, M.; Boeri, M.; Chorus, C.G.

2011-01-01

This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the

Counterfactual reasoning for regretted situations involving controllable versus uncontrollable events: the modulating role of contingent self-esteem.

Science.gov (United States)

Wilkinson, Meredith R; Ball, Linden J; Alford, David

2015-01-01

We report a study that examined the modulating impact of contingent self-esteem on regret intensity for regretted outcomes associated with controllable versus uncontrollable events. The Contingent Self-Esteem Scale (e.g., Kernis & Goldman, 2006) was used to assess the extent to which a person's sense of self-worth is based on self and others' expectations. We found that there was an influence of self-esteem contingency for controllable but not for uncontrollable regret types. For controllable regret types individuals with a high contingent (i.e., unstable) self-esteem reported greater regret intensity than those with a low contingent (i.e., stable) self-esteem. We interpret this finding as reflecting a functional and adaptive role of high contingent self-esteem in terms of mobilizing the application of counterfactual reasoning and planning mechanisms that can enable personal expectations to be achieved in the future.

Optimal choice of word length when comparing two Markov sequences using a χ 2-statistic.

Science.gov (United States)

Bai, Xin; Tang, Kujin; Ren, Jie; Waterman, Michael; Sun, Fengzhu

2017-10-03

Alignment-free sequence comparison using counts of word patterns (grams, k-tuples) has become an active research topic due to the large amount of sequence data from the new sequencing technologies. Genome sequences are frequently modelled by Markov chains and the likelihood ratio test or the corresponding approximate χ 2 -statistic has been suggested to compare two sequences. However, it is not known how to best choose the word length k in such studies. We develop an optimal strategy to choose k by maximizing the statistical power of detecting differences between two sequences. Let the orders of the Markov chains for the two sequences be r 1 and r 2 , respectively. We show through both simulations and theoretical studies that the optimal k= max(r 1 ,r 2 )+1 for both long sequences and next generation sequencing (NGS) read data. The orders of the Markov chains may be unknown and several methods have been developed to estimate the orders of Markov chains based on both long sequences and NGS reads. We study the power loss of the statistics when the estimated orders are used. It is shown that the power loss is minimal for some of the estimators of the orders of Markov chains. Our studies provide guidelines on choosing the optimal word length for the comparison of Markov sequences.

A systematic review of women's satisfaction and regret following risk-reducing mastectomy.

Science.gov (United States)

Braude, Lucy; Kirsten, Laura; Gilchrist, Jemma; Juraskova, Ilona

2017-12-01

A systematic review of quantitative and qualitative studies, to describe patient satisfaction and regret associated with risk-reducing mastectomies (RRM), and the patient-reported factors associated with these among women at high risk of developing breast cancer. Studies were identified using Medline, CINAHL, Embase and PsycInfo databases (1995-2016). Data were extracted and crosschecked for accuracy. Article quality was assessed using standardised criteria. Of the 1657 unique articles identified, 30 studies met the inclusion criteria (n=23 quantitative studies, n=3 qualitative studies, n=4 mixed-method studies). Studies included were cross-sectional (n=23) or retrospective (n=7). General satisfaction with RRM, decision satisfaction and aesthetic satisfaction were generally high, although some women expressed regret around their decision and dissatisfaction with their appearance. Factors associated with both patient satisfaction and regret included: post-operative complications, body image changes, psychological distress and perceived inadequacy of information. While satisfaction with RRM was generally high, some women had regrets and expressed dissatisfaction. Future research is needed to further explore RRM, and to investigate current satisfaction trends given the ongoing improvements to surgical and clinical practice. Offering pre-operative preparation, decisional support and continuous psychological input may help to facilitate satisfaction with this complex procedure. Copyright © 2017 Elsevier B.V. All rights reserved.

Counterfactual Reasoning for Regretted Situations Involving Controllable Versus Uncontrollable Events: The Modulating Role of Contingent Self-Esteem

Science.gov (United States)

Wilkinson, Meredith R.; Ball, Linden J.; Alford, David

2015-01-01

We report a study that examined the modulating impact of contingent self-esteem on regret intensity for regretted outcomes associated with controllable versus uncontrollable events. The Contingent Self-Esteem Scale (e.g., Kernis & Goldman, 2006) was used to assess the extent to which a person’s sense of self-worth is based on self and others’ expectations. We found that there was an influence of self-esteem contingency for controllable but not for uncontrollable regret types. For controllable regret types individuals with a high contingent (i.e., unstable) self-esteem reported greater regret intensity than those with a low contingent (i.e., stable) self-esteem. We interpret this finding as reflecting a functional and adaptive role of high contingent self-esteem in terms of mobilizing the application of counterfactual reasoning and planning mechanisms that can enable personal expectations to be achieved in the future. PMID:25883697

The application of the random regret minimization model to drivers’ choice of crash avoidance maneuvers

DEFF Research Database (Denmark)

Kaplan, Sigal; Prato, Carlo Giacomo

This study explores the plausibility of regret minimization as behavioral paradigm underlying the choice of crash avoidance maneuvers. Alternatively to previous studies that considered utility maximization, this study applies the random regret minimization (RRM) model while assuming that drivers ...

The application of the random regret minimization model to drivers’ choice of crash avoidance maneuvers

DEFF Research Database (Denmark)

Kaplan, Sigal; Prato, Carlo Giacomo

2012-01-01

This study explores the plausibility of regret minimization as behavioral paradigm underlying the choice of crash avoidance maneuvers. Alternatively to previous studies that considered utility maximization, this study applies the random regret minimization (RRM) model while assuming that drivers ...

Nocturnal Regrets and Insomnia in Elderly People

Science.gov (United States)

Schmidt, Ralph E.; Renaud, Olivier; Van Der Linden, Martial

2011-01-01

Despite their importance for general health, emotion-related factors have rarely been considered in the etiology of late-life insomnia. This study explored the relations between impulsivity, regret experiences, use of different thought-control strategies, and insomnia severity in a sample of older adults whose age ranged from 51 to 98 years.…

Reversal Surgery in Regretful Male-to-Female Transsexuals After Sex Reassignment Surgery.

Science.gov (United States)

Djordjevic, Miroslav L; Bizic, Marta R; Duisin, Dragana; Bouman, Mark-Bram; Buncamper, Marlon

2016-06-01

Sex reassignment surgery (SRS) has proved an effective intervention for patients with gender identity disorder. However, misdiagnosed patients sometimes regret their decision and request reversal surgery. This review is based on our experience with seven patients who regretted their decision to undergo male-to-female SRS. To analyze retrospectively seven patients who underwent reversal surgery after regretting their decision to undergo male-to-female SRS elsewhere. From November 2010 through November 2014, seven men 33 to 53 years old with previous male-to-female SRS underwent reversal phalloplasty. Preoperatively, they were examined by three independent psychiatrists. Surgery included three steps: removal of female genitalia with scrotoplasty and urethral lengthening, total phalloplasty with microvascular transfer of a musculocutaneous latissimus dorsi flap, and neophallus urethroplasty with penile prosthesis implantation. Self-reported esthetic and psychosexual status after reversion surgery and International Index of Erectile Function scores for sexual health after phalloplasty and penile prosthesis implantation. Follow-up was 13 to 61 months (mean = 31 months). Good postoperative results were achieved in all patients. In four patients, all surgical steps were completed; two patients are currently waiting for penile implants; and one patient decided against the penile prosthesis. Complications were related to urethral lengthening: two fistulas and one stricture were observed. All complications were repaired by minor revision. According to patients' self-reports, all patients were pleased with the esthetic appearance of their genitalia and with their significantly improved psychological status. Reversal surgery in regretful male-to-female transsexuals after SRS represents a complex, multistage procedure with satisfactory outcomes. Further insight into the characteristics of persons who regret their decision postoperatively would facilitate better future

Spectral analysis of multi-dimensional self-similar Markov processes

International Nuclear Information System (INIS)

Modarresi, N; Rezakhah, S

2010-01-01

In this paper we consider a discrete scale invariant (DSI) process {X(t), t in R + } with scale l > 1. We consider a fixed number of observations in every scale, say T, and acquire our samples at discrete points α k , k in W, where α is obtained by the equality l = α T and W = {0, 1, ...}. We thus provide a discrete time scale invariant (DT-SI) process X(.) with the parameter space {α k , k in W}. We find the spectral representation of the covariance function of such a DT-SI process. By providing the harmonic-like representation of multi-dimensional self-similar processes, spectral density functions of them are presented. We assume that the process {X(t), t in R + } is also Markov in the wide sense and provide a discrete time scale invariant Markov (DT-SIM) process with the above scheme of sampling. We present an example of the DT-SIM process, simple Brownian motion, by the above sampling scheme and verify our results. Finally, we find the spectral density matrix of such a DT-SIM process and show that its associated T-dimensional self-similar Markov process is fully specified by {R H j (1), R j H (0), j = 0, 1, ..., T - 1}, where R H j (τ) is the covariance function of jth and (j + τ)th observations of the process.

Comparison of Langevin and Markov channel noise models for neuronal signal generation.

Science.gov (United States)

Sengupta, B; Laughlin, S B; Niven, J E

2010-01-01

The stochastic opening and closing of voltage-gated ion channels produce noise in neurons. The effect of this noise on the neuronal performance has been modeled using either an approximate or Langevin model based on stochastic differential equations or an exact model based on a Markov process model of channel gating. Yet whether the Langevin model accurately reproduces the channel noise produced by the Markov model remains unclear. Here we present a comparison between Langevin and Markov models of channel noise in neurons using single compartment Hodgkin-Huxley models containing either Na+ and K+, or only K+ voltage-gated ion channels. The performance of the Langevin and Markov models was quantified over a range of stimulus statistics, membrane areas, and channel numbers. We find that in comparison to the Markov model, the Langevin model underestimates the noise contributed by voltage-gated ion channels, overestimating information rates for both spiking and nonspiking membranes. Even with increasing numbers of channels, the difference between the two models persists. This suggests that the Langevin model may not be suitable for accurately simulating channel noise in neurons, even in simulations with large numbers of ion channels.

Decisive Markov Chains

OpenAIRE

Abdulla, Parosh Aziz; Henda, Noomene Ben; Mayr, Richard

2007-01-01

We consider qualitative and quantitative verification problems for infinite-state Markov chains. We call a Markov chain decisive w.r.t. a given set of target states F if it almost certainly eventually reaches either F or a state from which F can no longer be reached. While all finite Markov chains are trivially decisive (for every set F), this also holds for many classes of infinite Markov chains. Infinite Markov chains which contain a finite attractor are decisive w.r.t. every set F. In part...

Emotional Reactions to the Outcomes of Decisions: The Role of Counterfactual Thought in the Experience of Regret and Disappointment.

Science.gov (United States)

Zeelenberg; van Dijk WW; van der Pligt J; Manstead; van Empelen P; Reinderman

1998-08-01

Regret and disappointment are emotions that can be experienced in response to an unfavorable outcome of a decision. Previous research suggests that both emotions are related to the process of counterfactual thinking. The present research extends this idea by combining it with ideas from regret and disappointment theory. The results show that regret is related to behavior-focused counterfactual thought in which the decision-maker's own actions are changed, whereas disappointment is related to situation-focused counterfactual thought in which aspects of the situation are changed. In Study 1 participants (N = 130) were asked to recall an autobiographical episode of either a regretful or a disappointing event. When asked to undo this event, regret participants predominantly changed their own actions, whereas disappointment participants predominantly changed aspects of the situation. In Study 2 all participants (N = 50) read a scenario in which a person experiences a negative event. Participants who were instructed to undo the event by changing the person's actions reported more regret than disappointment, while participants who were instructed to undo the event by changing aspects of the situation reported more disappointment than regret. Study 3 (N = 140) replicated the findings from Study 2 with a different scenario, and a design in which regret and disappointment were measured between rather than within subjects. In the discussion we address the relation among counterfactual thinking, attributions and affective reactions to decision outcomes, and the implications for decision research. Copyright 1998 Academic Press.

Investor regret: The role of expectation in comparing what is to what might have been

Directory of Open Access Journals (Sweden)

Wen-Hsien Huang

2012-07-01

Full Text Available Investors, like any decision maker, feel regret when they compare the outcome of an investment with what the outcome would have been had they invested differently. We argue and show that this counterfactual comparison process is most likely to take place when the decision maker's expectations are violated. Across five scenario experiments we found that decision makers were influenced only by forgone investment outcomes when the realized investment fell short of the expected result. However, when their investments exceeded prior expectations, the effect of foregone investment on regret disappeared. In addition, Experiment 4 found that individual differences in the need to maximize further moderated the effects of their expectations, such that maximizers always take into account the forgone investment. The final experiment found that when probed to make counterfactual comparisons, also investments that exceed expectations may lead to regret. Together these experiments reveal insights into the comparative processes leading to decision regret.

A relation between non-Markov and Markov processes

International Nuclear Information System (INIS)

Hara, H.

1980-01-01

With the aid of a transformation technique, it is shown that some memory effects in the non-Markov processes can be eliminated. In other words, some non-Markov processes are rewritten in a form obtained by the random walk process; the Markov process. To this end, two model processes which have some memory or correlation in the random walk process are introduced. An explanation of the memory in the processes is given. (orig.)

The importance of regret minimization in the choice for renewable energy programmes: Evidence from a discrete choice experiment

International Nuclear Information System (INIS)

Boeri, Marco; Longo, Alberto

2017-01-01

This study provides a methodologically rigorous attempt to disentangle the impact of various factors – unobserved heterogeneity, information and environmental attitudes – on the inclination of individuals to exhibit either a utility maximization or a regret minimization behaviour in a discrete choice experiment for renewable energy programmes described by four attributes: greenhouse gas emissions, power outages, employment in the energy sector, and electricity bill. We explore the ability of different models – multinomial logit, random parameters logit, and hybrid latent class – and of different choice paradigms – utility maximization and regret minimization – in explaining people's choices for renewable energy programmes. The “pure” random regret random parameters logit model explains the choices of our respondents better than other models, indicating that regret is an important choice paradigm, and that choices for renewable energy programmes are mostly driven by regret, rather than by rejoice. In particular, we find that our respondents' choices are driven more by changes in greenhouse gas emissions than by reductions in power outages. Finally, we find that changing the level of information to one attribute has no effect on choices, and that being a member of an environmental organization makes a respondent more likely to be associated with the utility maximization choice framework. - Highlights: • The first paper to use the Random Regret Minimization choice paradigm in energy economics • With a hybrid latent class model, choices conform to either utility or pure random regret. • The pure random regret random parameters logit model outperforms other models. • Reducing greenhouse gas emissions is more important than reducing power outages.

Regret and rationalization among smokers in Thailand and Malaysia: findings from the International Tobacco Control Southeast Asia Survey.

Science.gov (United States)

Lee, Wonkyong B; Fong, Geoffrey T; Zanna, Mark P; Omar, Maizurah; Sirirassamee, Buppha; Borland, Ron

2009-07-01

To test whether differences of history and strength in tobacco control policies will influence social norms, which, in turn, will influence quit intentions, by influencing smokers' regret and rationalization. The data were from the International Tobacco Control (ITC) Policy Evaluation Southeast Asia Survey, a cohort survey of representative samples of adult smokers in Thailand (N = 2,000) and Malaysia (N = 2,006). The survey used a stratified multistage sampling design. Measures included regret, rationalization, social norms, and quit intention. Thai smokers were more likely to have quit intentions than Malaysian smokers. This difference in quit intentions was, in part, explained by the country differences in social norms, regret, and rationalization. Reflecting Thailand's history of stronger tobacco control policies, Thai smokers, compared with Malaysian smokers, perceived more negative social norms toward smoking, were more likely to regret, and less likely to rationalize smoking. Mediational analyses revealed that these differences in social norms, accounted, in part, for the country-quit intention relation and that regret and rationalization accounted, in part, for the social norm-quit intention relation. The results suggest that social norms toward smoking, which are shaped by tobacco control policies, and smokers' regret and rationalization influence quit intentions.

Protecting young children against skin cancer: Parental beliefs, roles, and regret.

Science.gov (United States)

Hamilton, Kyra; Kirkpatrick, Aaron; Rebar, Amanda; White, Katherine M; Hagger, Martin S

2017-12-01

To examine the role of parental beliefs, roles, and anticipated regret toward performing childhood sun-protective behaviours. Parents (N = 230; 174 mothers, 56 fathers), recruited using a nonrandom convenience sample, of at least 1 child aged between 2 and 5 years completed an initial questionnaire assessing demographics and past behaviour as well as theory of planned behaviour global (attitude, subjective norm, and perceived behavioural control) and belief-based (behavioural, normative, and control beliefs) measures, role construction, and anticipated regret regarding their intention and behaviour to protect their child from the sun. Two weeks later, participants completed a follow-up questionnaire assessing their sun protection of their child during the previous 2 weeks. Hierarchical multiple regression analysis identified attitude, perceived behavioural control, role construction, anticipated regret, past behaviour, and a normative belief ("current partner/other family members") as significant predictors of parents' intention to participate in sun-protective behaviour for their child. Intention and past behaviour were significant predictors of parents' follow-up sun-protective behaviour. The regression models explained 64% and 36% of the variance in intention and behaviour, respectively. The findings of this study highlight the importance of anticipated regret and role-related beliefs alongside personal, normative, and control beliefs in determining parents' intentional sun-protective behaviour for their children. Findings may inform the development of parent- and community-based sun protection intervention programs to promote parents' sun-safety behaviours for their children to prevent future skin cancer incidence. Copyright © 2017 John Wiley & Sons, Ltd.

Every third Kazakhstani medical student regrets the choice of ...

African Journals Online (AJOL)

admin

Conclusions: The results suggest that one third of medical students in Almaty, Kazakhstan, regret the choice of medical education. ..... test (MCAT) (24), the graduate Australian medical .... experience of help seeking for mental health problems ...

Markov stochasticity coordinates

International Nuclear Information System (INIS)

Eliazar, Iddo

2017-01-01

Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.

Markov stochasticity coordinates

Energy Technology Data Exchange (ETDEWEB)

Eliazar, Iddo, E-mail: iddo.eliazar@intel.com

2017-01-15

Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.

On the Metric-based Approximate Minimization of Markov Chains

DEFF Research Database (Denmark)

Bacci, Giovanni; Bacci, Giorgio; Larsen, Kim Guldstrand

2018-01-01

In this paper we address the approximate minimization problem of Markov Chains (MCs) from a behavioral metric-based perspective. Specifically, given a finite MC and a positive integer k, we are looking for an MC with at most k states having minimal distance to the original. The metric considered...

Treatment Decision Regret Among Long-Term Survivors of Localized Prostate Cancer: Results From the Prostate Cancer Outcomes Study.

Science.gov (United States)

Hoffman, Richard M; Lo, Mary; Clark, Jack A; Albertsen, Peter C; Barry, Michael J; Goodman, Michael; Penson, David F; Stanford, Janet L; Stroup, Antoinette M; Hamilton, Ann S

2017-07-10

Purpose To determine the demographic, clinical, decision-making, and quality-of-life factors that are associated with treatment decision regret among long-term survivors of localized prostate cancer. Patients and Methods We evaluated men who were age ≤ 75 years when diagnosed with localized prostate cancer between October 1994 and October 1995 in one of six SEER tumor registries and who completed a 15-year follow-up survey. The survey obtained demographic, socioeconomic, and clinical data and measured treatment decision regret, informed decision making, general- and disease-specific quality of life, health worry, prostate-specific antigen (PSA) concern, and outlook on life. We used multivariable logistic regression analyses to identify factors associated with regret. Results We surveyed 934 participants, 69.3% of known survivors. Among the cohort, 59.1% had low-risk tumor characteristics (PSA decision regret: 8.2% of those whose disease was managed conservatively, 15.0% of those who received surgery, and 16.6% of those who underwent radiotherapy. Factors associated with regret on multivariable analysis included reporting moderate or big sexual function bother (reported by 39.0%; OR, 2.77; 95% CI, 1.51 to 5.0), moderate or big bowel function bother (reported by 7.7%; OR, 2.32; 95% CI, 1.04 to 5.15), and PSA concern (mean score 52.8; OR, 1.01 per point change; 95% CI, 1.00 to 1.02). Increasing age at diagnosis and report of having made an informed treatment decision were inversely associated with regret. Conclusion Regret was a relatively infrequently reported outcome among long-term survivors of localized prostate cancer; however, our results suggest that better informing men about treatment options, in particular, conservative treatment, might help mitigate long-term regret. These findings are timely for men with low-risk cancers who are being encouraged to consider active surveillance.

No-Regrets Remodeling, 2nd Edition

Energy Technology Data Exchange (ETDEWEB)

None

2013-12-01

No-Regrets Remodeling, sponsored by Oak Ridge National Laboratory, is an informative publication that walks homeowners and/or remodelers through various home remodeling projects. In addition to remodeling information, the publication provides instruction on how to incorporate energy efficiency into the remodeling process. The goal of the publication is to improve homeowner satisfaction after completing a remodeling project and to provide the homeowner with a home that saves energy and is comfortable and healthy.

The "ick" factor, anticipated regret, and willingness to become an organ donor.

Science.gov (United States)

O'Carroll, Ronan E; Foster, Catherine; McGeechan, Grant; Sandford, Kayleigh; Ferguson, Eamonn

2011-03-01

This research tested the role of traditional rational-cognitive factors and emotional barriers to posthumous organ donation. An example of an emotional barrier is the "ick" factor, a basic disgust reaction to the idea of organ donation. We also tested the potential role of manipulating anticipated regret to increase intention to donate in people who are not yet registered organ donors. In three experiments involving 621 members of the United Kingdom general public, participants were invited to complete questionnaire measures tapping potential emotional affective attitude barriers such as the "ick" factor, the desire to retain bodily integrity after death, and medical mistrust. Registered posthumous organ donors were compared with nondonors. In Experiments 2 and 3, nondonors were then allocated to a simple anticipated regret manipulation versus a control condition, and the impact on intention to donate was tested. Self-reported emotional barriers and intention to donate in the future. Traditional rational-cognitive factors such as knowledge, attitude, and subjective norm failed to distinguish donors from nondonors. However, in all three experiments, nondonors scored significantly higher than donors on the emotional "ick" factor and bodily integrity scales. A simple anticipated regret manipulation led to a significant increase in intention to register as an organ donor in future. Negative affective attitudes are thus crucial barriers to people registering as organ donors. A simple anticipated regret manipulation has the potential to significantly increase organ donation rates. (c) 2011 APA, all rights reserved

Validation of a 10-item care-related regret intensity scale (RIS-10) for health care professionals.

Science.gov (United States)

Courvoisier, Delphine S; Cullati, Stéphane; Haller, Chiara S; Schmidt, Ralph E; Haller, Guy; Agoritsas, Thomas; Perneger, Thomas V

2013-03-01

Regret after one of the many decisions and interventions that health care professionals make every day can have an impact on their own health and quality of life, and on their patient care practices. To validate a new care-related regret intensity scale (RIS) for health care professionals. Retrospective cross-sectional cohort study with a 1-month follow-up (test-retest) in a French-speaking University Hospital. A total of 469 nurses and physicians responded to the survey, and 175 answered the retest. RIS, self-report questions on the context of the regret-inducing event, its consequences for the patient, involvement of the health care professionals, and changes in patient care practices after the event. We measured the impact of regret intensity on health care professionals with the satisfaction with life scale, the SF-36 first question (self-reported health), and a question on self-esteem. On the basis of factor analysis and item response analysis, the initial 19-item scale was shortened to 10 items. The resulting scale (RIS-10) was unidimensional and had high internal consistency (α=0.87) and acceptable test-retest reliability (0.70). Higher regret intensity was associated with (a) more consequences for the patient; (b) lower life satisfaction and poorer self-reported health in health care professionals; and (c) changes in patient care practices. Nurses reported analyzing the event and apologizing, whereas physicians reported talking preferentially to colleagues, rather than to their supervisor, about changing practices. The RIS is a valid and reliable measure of care-related regret intensity for hospital-based physicians and nurses.

Regret about surgical decisions among early-stage breast cancer patients: Effects of the congruence between patients' preferred and actual decision-making roles.

Science.gov (United States)

Wang, Ashley Wei-Ting; Chang, Su-Mei; Chang, Cheng-Shyong; Chen, Shou-Tung; Chen, Dar-Ren; Fan, Fang; Antoni, Michael H; Hsu, Wen-Yau

2018-02-01

Early-stage breast cancer patients generally receive either a mastectomy or a lumpectomy, either by their own choice or that of their surgeon. Sometimes, there is regret about the decision afterward. To better understand regret about surgical decisions, this study examined 2 possibilities: The first is that women who take a dominant or collaborative role in decision making about the surgery express less regret afterward. The second is that congruence between preferred role and actual role predicts less regret. We also explored whether disease stage moderates the relationship between role congruence and decisional regret. In a cross-sectional design, 154 women diagnosed with breast cancer completed a survey assessing decisional role preference and actual decisional role, a measure of post-decision regret, and a measure of disturbances related to breast cancer treatment. Hierarchical regression was used to investigate prediction of decisional regret. Role congruence, not actual decisional role, was significantly associated with less decisional regret, independent of all the control variables. The interaction between disease stage and role congruence was also significant, showing that mismatch relates to regret only in women with more advanced disease. Our findings suggest that cancer patients could benefit from tailored decision support concerning their decisional role preferences in the complex scenario of medical and personal factors during the surgical decision. Copyright © 2017 John Wiley & Sons, Ltd.

On the Metric-Based Approximate Minimization of Markov Chains

DEFF Research Database (Denmark)

Bacci, Giovanni; Bacci, Giorgio; Larsen, Kim Guldstrand

2017-01-01

We address the behavioral metric-based approximate minimization problem of Markov Chains (MCs), i.e., given a finite MC and a positive integer k, we are interested in finding a k-state MC of minimal distance to the original. By considering as metric the bisimilarity distance of Desharnais at al...

Counterfactually Mediated Emotions: A Developmental Study of Regret and Relief in a Probabilistic Gambling Task

Science.gov (United States)

Habib, M.; Cassotti, M.; Borst, G.; Simon, G.; Pineau, A.; Houde, O.; Moutier, S.

2012-01-01

Regret and relief are related to counterfactual thinking and rely on comparison processes between what has been and what might have been. In this article, we study the development of regret and relief from late childhood to adulthood (11.2-20.2 years), and we examine how these two emotions affect individuals' willingness to retrospectively…

An Experimental Decision-Making Paradigm to Distinguish Guilt and Regret and Their Self-Regulating Function via Loss Averse Choice Behavior.

Science.gov (United States)

Wagner, Ullrich; Handke, Lisa; Dörfel, Denise; Walter, Henrik

2012-01-01

Both guilt and regret typically result from counterfactual evaluations of personal choices that caused a negative outcome and are thought to regulate human decisions by people's motivation to avoid these emotions. Despite these similarities, studies asking people to describe typical situations of guilt and regret identified the social dimension as a fundamental distinguishing factor, showing that guilt but not regret specifically occurs for choices in interpersonal (social) contexts. However, an experimental paradigm to investigate this distinction systematically by inducing emotions of guilt and regret online is still missing. Here, extending existing procedures, we introduce such a paradigm, in which participants choose in each trial between two lotteries, with the outcome of the chosen lottery (gain or loss) being either assigned to themselves (intrapersonal trials) or to another person (interpersonal trials). After results of both the chosen and the unchosen lottery were shown, subjects rated how they felt about the outcome, including ratings of guilt and regret. Trait Guilt (TG) was determined for all participants in order to take their general inclination to experience guilt into account. Results confirmed that guilt but not regret specifically occurred in an interpersonal context. Percentages of loss averse choices (choosing the lottery with the lower possible monetary loss) were determined as indicators of regulation via guilt and regret avoidance. High TG scorers generally made more loss averse choices than low TG scorers, while trial-by-trial analyses showed that low TG scorers used their feelings of guilt more specifically to avoid the same emotional experience in subsequent choices. Our results confirm the social dimension as the critical factor distinguishing guilt from regret and identify TG as an important moderator determining the way in which guilt vs. regret can regulate their own occurrence by influencing choice strategies.

An experimental decision-making paradigm to distinguish guilt and regret and their self-regulating function via loss-averse choice behavior

Directory of Open Access Journals (Sweden)

Ullrich eWagner

2012-10-01

Full Text Available Both guilt and regret typically result from counterfactual evaluations of personal choices that caused a negative outcome and are thought to regulate human decisions by people’s motivation to avoid these emotions. Despite these similarities, studies asking people to describe typical situations of guilt and regret identified the social dimension as a fundamental distinguishing factor, showing that guilt but not regret specifically occurs for choices in interpersonal (social contexts. However, an experimental paradigm to investigate this distinction systematically by inducing emotions of guilt and regret online is still missing. Here, extending existing procedures, we introduce such a paradigm, in which participants choose in each trial between two lotteries, with the outcome of the chosen lottery (gain or loss being either assigned to themselves (intrapersonal trials or to another person (interpersonal trials. After results of both the chosen and the unchosen lottery were shown, subjects rated how they felt about the outcome, including ratings of guilt and regret. Trait Guilt (TG was determined for all participants in order to take their general inclination to experience guilt into account. Results confirmed that guilt but not regret specifically occurred in an interpersonal context. Percentages of loss averse choices (choosing the lottery with the lower possible monetary loss were determined as indicators of regulation via guilt and regret avoidance. High TG scorers generally made more loss averse choices than low TG scorers, while trial-by-trial analyses showed that low TG scorers used their feelings of guilt more specifically to avoid the same emotional experience in subsequent choices. Our results confirm the social dimension as the critical factor distinguishing guilt from regret and identify TG as an important moderator determining the way in which guilt vs. regret can regulate their own occurrence by influencing choice strategies.

An Experimental Decision-Making Paradigm to Distinguish Guilt and Regret and Their Self-Regulating Function via Loss Averse Choice Behavior

Science.gov (United States)

Wagner, Ullrich; Handke, Lisa; Dörfel, Denise; Walter, Henrik

2012-01-01

Both guilt and regret typically result from counterfactual evaluations of personal choices that caused a negative outcome and are thought to regulate human decisions by people’s motivation to avoid these emotions. Despite these similarities, studies asking people to describe typical situations of guilt and regret identified the social dimension as a fundamental distinguishing factor, showing that guilt but not regret specifically occurs for choices in interpersonal (social) contexts. However, an experimental paradigm to investigate this distinction systematically by inducing emotions of guilt and regret online is still missing. Here, extending existing procedures, we introduce such a paradigm, in which participants choose in each trial between two lotteries, with the outcome of the chosen lottery (gain or loss) being either assigned to themselves (intrapersonal trials) or to another person (interpersonal trials). After results of both the chosen and the unchosen lottery were shown, subjects rated how they felt about the outcome, including ratings of guilt and regret. Trait Guilt (TG) was determined for all participants in order to take their general inclination to experience guilt into account. Results confirmed that guilt but not regret specifically occurred in an interpersonal context. Percentages of loss averse choices (choosing the lottery with the lower possible monetary loss) were determined as indicators of regulation via guilt and regret avoidance. High TG scorers generally made more loss averse choices than low TG scorers, while trial-by-trial analyses showed that low TG scorers used their feelings of guilt more specifically to avoid the same emotional experience in subsequent choices. Our results confirm the social dimension as the critical factor distinguishing guilt from regret and identify TG as an important moderator determining the way in which guilt vs. regret can regulate their own occurrence by influencing choice strategies. PMID:23133433

A regret theory approach to decision curve analysis: a novel method for eliciting decision makers' preferences and decision-making.

Science.gov (United States)

Tsalatsanis, Athanasios; Hozo, Iztok; Vickers, Andrew; Djulbegovic, Benjamin

2010-09-16

Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat) vs. "commissions" (e.g. treating unnecessary) and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may be intuitively more appealing to a decision-maker, particularly

Personal responsibility, regret, and medical stigma among individuals living with lung cancer.

Science.gov (United States)

Criswell, Kevin R; Owen, Jason E; Thornton, Andrea A; Stanton, Annette L

2016-04-01

Understanding the degree to which adults with lung cancer perceive personal responsibility for their disease, personal regret for actions that may have contributed to lung cancer, and potential stigmatization from others is important, because these perceptions and experiences may be linked with treatment nonadherence, feelings of isolation, avoidance of healthcare providers, and poor quality of life. The purpose of this study was to evaluate rates and intensity of these types of experiences and to characterize the extent to which they are linked with smoking status and psychological adjustment in those living with lung cancer. Adults with lung cancer (N = 213) were recruited from two major cancer centers to complete a mail survey. Perceived responsibility was frequent in those who had ever smoked (74-80%), whereas regret and feelings of stigmatization were less frequent. When present, however, personal regret and stigmatization were associated with adverse psychological outcomes, particularly for never smokers. These results are consistent with the theory of stereotype threat and have clinical implications for management of people with lung cancer.

Inaction inertia, regret, and valuation : A closer look

NARCIS (Netherlands)

Zeelenberg, Marcel; Nijstad, Bernard A.; van Putten, Marijke; van Dijk, Eric

Inaction inertia is the phenomenon that one is not likely to act on an attractive opportunity after having bypassed an even more attractive opportunity. So far, all published work has assumed a causal role for the emotion regret in this effect. In a series of 5 experiments we found no support for

Opportunity, satisfaction and regret: trying long acting reversible contraception in a unique scientific circumstance.

Science.gov (United States)

Burke, Holly M; Packer, Catherine A; Spector, Hannah L; Hubacher, David

2018-06-19

Increased use of long-acting reversible contraception (LARC) can reduce unintended pregnancies. However, significant barriers exist to LARC uptake, particularly high up-front costs. In North Carolina in 2014, we interviewed 34 purposively-selected participants (aged 20-30 years) enrolled in a partially randomized patient preference trial to learn about their experiences with and attitudes toward contraception in this unique trial context. Cost of LARC was important in participants' decision-making. Experiencing an unintended pregnancy motivated women to switch to LARC. No participants who tried LARC, even those who experienced side effects, regretted it. Several participants regretted discontinuing their LARC. Concerns about insertion and removal did not influence future willingness to try LARC. Participants discussed the importance of affordability and feeling in control when choosing a contraceptive method. Cost, combined with uncertainty over whether LARC is the right method for them, may deter young women from trying LARC. Intrauterine devices and implants should be made affordable so that women can try them without significant financial commitment. Affordability will likely increase uptake, which will reduce unintended pregnancies. Regret from discontinuing LARC was more more frequently reported than regret from trying LARC. Providers should offer young women LARC and counsel to support continuation.

Semi-Markov processes

CERN Document Server

Grabski

2014-01-01

Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time semi-Markov processes and their applications in reliability and maintenance. The book explains how to construct semi-Markov models and discusses the different reliability parameters and characteristics that can be obtained from those models. The book is a useful resource for mathematicians, engineering practitioners, and PhD and MSc students who want to understand the basic concepts and results of semi-Markov process theory. Clearly defines the properties and

K­MEANS CLUSTERING FOR HIDDEN MARKOV MODEL

NARCIS (Netherlands)

Perrone, M.P.; Connell, S.D.

2004-01-01

An unsupervised k­means clustering algorithm for hidden Markov models is described and applied to the task of generating subclass models for individual handwritten character classes. The algorithm is compared to a related clustering method and shown to give a relative change in the error rate of as

Satisfaction with treatment decision-making and treatment regret among Latinas and non-Latina whites with DCIS

Science.gov (United States)

López, Mónica E.; Kaplan, Celia P.; Nápoles, Anna M.; Hwang, E. Shelly; Livaudais, Jennifer C.; Karliner, Leah S.

2013-01-01

Objective To examine differences in treatment decision-making participation, satisfaction, and regret among Latinas and non-Latina whites with DCIS. Methods Survey of Latina and non-Latina white women diagnosed with DCIS. We assessed women’s preferences for involvement in decision-making, primary treatment decision maker, and participatory decision-making. We examined primary outcomes of satisfaction with treatment decision-making and treatment regret by ethnic-language group. Results Among 745 participants (349 Latinas, 396 white) Spanish-speaking Latinas (SSL) had the highest mean preference for involvement in decision-making score and the lowest mean participatory decision-making score and were more likely to defer their final treatment decision to their physicians than English-speaking Latinas or whites (26%, 13%, 18%, pdecision-making (OR 0.4; CI 95%, 0.2-0.8) and expressed more regret than whites (OR 6.2; CI 95%, 3.0-12.4). More participatory decision-making increased the odds of satisfaction (OR 1.5; CI 95%, 1.3-1.8) and decreased the odds of treatment regret (OR 0.8; CI 95%, 0.7-1.0), independent of ethnicity-language. Conclusion Language barriers impede the establishment of decision-making partnerships between Latinas and their physicians, and result in less satisfaction with the decision-making process and more treatment regret. Practice Implications Use of professional interpreters may address communication-related disparities for these women. PMID:24207116

On the representability of complete genomes by multiple competing finite-context (Markov models.

Directory of Open Access Journals (Sweden)

Armando J Pinho

Full Text Available A finite-context (Markov model of order k yields the probability distribution of the next symbol in a sequence of symbols, given the recent past up to depth k. Markov modeling has long been applied to DNA sequences, for example to find gene-coding regions. With the first studies came the discovery that DNA sequences are non-stationary: distinct regions require distinct model orders. Since then, Markov and hidden Markov models have been extensively used to describe the gene structure of prokaryotes and eukaryotes. However, to our knowledge, a comprehensive study about the potential of Markov models to describe complete genomes is still lacking. We address this gap in this paper. Our approach relies on (i multiple competing Markov models of different orders (ii careful programming techniques that allow orders as large as sixteen (iii adequate inverted repeat handling (iv probability estimates suited to the wide range of context depths used. To measure how well a model fits the data at a particular position in the sequence we use the negative logarithm of the probability estimate at that position. The measure yields information profiles of the sequence, which are of independent interest. The average over the entire sequence, which amounts to the average number of bits per base needed to describe the sequence, is used as a global performance measure. Our main conclusion is that, from the probabilistic or information theoretic point of view and according to this performance measure, multiple competing Markov models explain entire genomes almost as well or even better than state-of-the-art DNA compression methods, such as XM, which rely on very different statistical models. This is surprising, because Markov models are local (short-range, contrasting with the statistical models underlying other methods, where the extensive data repetitions in DNA sequences is explored, and therefore have a non-local character.

Validation of a 15-item care-related regret coping scale for health-care professionals (RCS-HCP).

Science.gov (United States)

Courvoisier, Delphine Sophie; Cullati, Stephane; Ouchi, Rieko; Schmidt, Ralph Eric; Haller, Guy; Chopard, Pierre; Agoritsas, Thomas; Perneger, Thomas V

2014-01-01

Coping with difficult care-related situations is a common challenge for health-care professionals. How these professionals deal with the regrets they may experience following one of the many decisions and interventions they must make every day can have an impact on their own health and quality of life, and also on their patient care practices. To identify professionals most at need for extra support, development and validation of a tool measuring coping style are needed. We performed a survey of physicians and nurses of a French-speaking University hospital; 469 health-care professionals responded to the survey, and 175 responded to the same survey one-month later. Regret was assessed with the regret coping scale developed for this study, self-report questions on the frequency of regretted situations and the intensity of regret. Construct validity was assessed using measures of health-care professionals' quality of life (including job and life satisfaction, and self-reported health) as well as sleep problems and depression. Based on factor analysis and item response analysis, the initial 31-item scale was shortened to 15 items, which measured three types of strategies: problem-focused strategies (i.e., trying to find solutions, talking to colleagues) and two types of emotion-focused strategies, A (i.e., self-blame, rumination) and B (e.g., acceptance, emotional distance). All subscales showed high internal consistency (α >0.85). Overall, as expected, problem-focused and emotion-focused B strategies correlated with higher quality of life, fewer sleep problems and less depression, and emotion-focused A strategies showed the opposite pattern. The regret coping scale (RCS-HCP) is a valid and reliable measure of coping abilities of hospital-based health-care professionals.

A regret theory approach to decision curve analysis: A novel method for eliciting decision makers' preferences and decision-making

Directory of Open Access Journals (Sweden)

Vickers Andrew

2010-09-01

Full Text Available Abstract Background Decision curve analysis (DCA has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1, and analytical, deliberative process (system 2, thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. Methods First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. Results We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat vs. "commissions" (e.g. treating unnecessary and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. Conclusions We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may

Increasing organ donation via anticipated regret (INORDAR: protocol for a randomised controlled trial

Directory of Open Access Journals (Sweden)

O'Carroll Ronan E

2012-03-01

Full Text Available Abstract Background Throughout the world there is an insufficient supply of donor organs to meet the demand for organ transplantations. This paper presents a protocol for a randomised controlled trial, testing whether a simple, theory-based anticipated regret manipulation leads to a significant increase in posthumous organ donor registrations. Methods We will use a between-groups, prospective randomised controlled design. A random sample of 14,520 members of the adult Scottish general public will be contacted via post. These participants will be randomly allocated into 1 of the 4 conditions. The no questionnaire control (NQC group will simply receive a letter and donor registration form. The questionnaire control (QC arm will receive a questionnaire measuring their emotions and non-cognitive affective attitudes towards organ donation. The theory of planned behavior (TPB group will complete the emotions and affective attitudes questionnaire plus additional items assessing their cognitive attitudes towards organ donation, perceived control over registration and how they think significant others view this action. Finally, the anticipated regret (AR group will complete the same indices as the TPB group, plus two additional anticipated regret items. These items will assess the extent to which the participant anticipates regret for not registering as an organ donor in the near future. The outcome variable will be NHS Blood and Transplant verified registrations as an organ donor within 6 months of receiving our postal intervention. Discussion This study will assess whether simply asking people to reflect on the extent to which they may anticipate regret for not registering as an organ donor increases organ donor registration 6 months later. If successful, this simple and easy to administer theory-based intervention has the potential to save lives and money for the NHS by reducing the number of people receiving treatments such as dialysis. This

An Experimental Decision-Making Paradigm to Distinguish Guilt and Regret and Their Self-Regulating Function via Loss Averse Choice Behavior

OpenAIRE

Wagner, Ullrich; Handke, Lisa; Dörfel, Denise; Walter, Henrik

2012-01-01

Both guilt and regret typically result from counterfactual evaluations of personal choices that caused a negative outcome and are thought to regulate human decisions by people’s motivation to avoid these emotions. Despite these similarities, studies asking people to describe typical situations of guilt and regret identified the social dimension as a fundamental distinguishing factor, showing that guilt but not regret specifically occurs for choices in interpersonal (social) contexts. However,...

Regret and Responsibility: A Reply to Zeelenberg et al. (1998).

Science.gov (United States)

Ordóñez; Connolly

2000-01-01

M. Zeelenberg, W. W. van Dijk, and A. S. R. Manstead (1998, Organizational Behavior and Human Decision Processes, 74, 254-272) recently reported an altered replication of our earlier study (T. Connolly, L. D. Ordóñez, & R. Coughlan, 1997, Organizational Behavior and Human Decision Processes, 70, 73-85) concerning the effects of decision agency on regret and outcome evaluation. Our earlier study had found no such effect, but Zeelenberg et al. did. In two new experiments, we have largely confirmed Zeelenberg et al.'s result but have shown that, contrary to most theory, regret (a) can appear even in the absence of decision agency, (b) can be unrelated to outcome evaluations, and (c) may be more influenced by the experience of gains or losses from the status quo than by any decisional responsibility for those changes. Copyright 2000 Academic Press.

Integrating Regret Psychology to Travel Mode Choice for a Transit-Oriented Evacuation Strategy

Directory of Open Access Journals (Sweden)

Shi An

2015-06-01

Full Text Available Facing the potential dangers from sudden disasters in urban cities, emergency administrators have to make an appropriate evacuation plan to mitigate negative consequences. However, little attention has been paid to evacuee real decision psychology when developing a strategy. The aim of this paper is to analyze evacuee mode choice behavior considering regret aversion psychology during evacuation. First, the utility-based and regret-based models are formulated to obtain evacuees’ preferences on travel mode choice, respectively. According to the data collected from the stated preference (SP survey on evacuee mode choice, the estimation results show that the regret-based model performs better than the utility model. Moreover, based on the estimates from behavioral analysis, the elasticities of evacuee mode choices are calculated, and transit strategy simulation is undertaken to investigate the influence on evacuee mode switching from private automobile to public transit. The results are expected to help emergency administrators to make a transit-oriented strategy for a sustainable evacuation plan, especially for the benefit of carless people.

Cerebellar damage impairs the self-rating of regret feeling in a gambling task

Science.gov (United States)

Clausi, Silvia; Coricelli, Giorgio; Pisotta, Iolanda; Pavone, Enea Francesco; Lauriola, Marco; Molinari, Marco; Leggio, Maria

2015-01-01

Anatomical, clinical, and neuroimaging evidence implicates the cerebellum in processing emotions and feelings. Moreover recent studies showed a cerebellar involvement in pathologies such as autism, schizophrenia and alexithymia, in which emotional processing have been found altered. However, cerebellar function in the modulation of emotional responses remains debated. In this study, emotions that are involved directly in decision-making were examined in 15 patients (six males; age range 17–60 years) affected by cerebellar damage and 15 well matched healthy controls. We used a gambling task, in which subjects’ choices and evaluation of outcomes with regard to their anticipated and actual emotional impact were analyzed. Emotions, such as regret and relief, were elicited, based on the outcome of the unselected gamble. Interestingly, despite their ability to avoid regret in subsequent choices, patients affected by cerebellar lesions were significantly impaired in evaluating the feeling of regret subjectively. These results demonstrate that the cerebellum is involved in conscious recognizing of negative feelings caused by the sense of self-responsibility for an incorrect decision. PMID:25999829

Turning university professors into competent learners

NARCIS (Netherlands)

Stefanova, Eliza; Ilieva, Miroslava; Nikolova, Nikolina; Stefanov, Krassen

2008-01-01

Stefanova, E., Ilieva, M., Nikolova, N, & Stefanov, K. (2008). Turning university professors into competent learners. In H. W. Sligte & R. Koper (Eds.), Proceedings of the 4th TENCompetence Open Workshop. Empowering Learners for Lifelong Competence Development: pedagogical, organisational and

Decision regret in men undergoing dose-escalated radiation therapy for prostate cancer.

Science.gov (United States)

Steer, Anna N; Aherne, Noel J; Gorzynska, Karen; Hoffman, Matthew; Last, Andrew; Hill, Jacques; Shakespeare, Thomas P

2013-07-15

Decision regret (DR) is a negative emotion associated with medical treatment decisions, and it is an important patient-centered outcome after therapy for localized prostate cancer. DR has been found to occur in up to 53% of patients treated for localized prostate cancer, and it may vary depending on treatment modality. DR after modern dose-escalated radiation therapy (DE-RT) has not been investigated previously, to our knowledge. Our primary aim was to evaluate DR in a cohort of patients treated with DE-RT. We surveyed 257 consecutive patients with localized prostate cancer who had previously received DE-RT, by means of a validated questionnaire. There were 220 responses (85.6% response rate). Image-guided intensity modulated radiation therapy was given in 85.0% of patients and 3-dimensional conformal radiation therapy in 15.0%. Doses received included 73.8 Gy (34.5% patients), 74 Gy (53.6%), and 76 Gy (10.9%). Neoadjuvant androgen deprivation (AD) was given in 51.8% of patients and both neoadjuvant and adjuvant AD in 34.5%. The median follow-up time was 23 months (range, 12-67 months). In all, 3.8% of patients expressed DR for their choice of treatment. When asked whether they would choose DE-RT or AD again, only 0.5% probably or definitely would not choose DE-RT again, compared with 8.4% for AD (P<.01). Few patients treated with modern DE-RT express DR, with regret appearing to be lower than in previously published reports of patients treated with radical prostatectomy or older radiation therapy techniques. Patients experienced more regret with the AD component of treatment than with the radiation therapy component, with implications for informed consent. Further research should investigate regret associated with individual components of modern therapy, including AD, radiation therapy and surgery. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

Decision Regret in Men Undergoing Dose-Escalated Radiation Therapy for Prostate Cancer

International Nuclear Information System (INIS)

Steer, Anna N.; Aherne, Noel J.; Gorzynska, Karen; Hoffman, Matthew; Last, Andrew; Hill, Jacques; Shakespeare, Thomas P.

2013-01-01

Purpose: Decision regret (DR) is a negative emotion associated with medical treatment decisions, and it is an important patient-centered outcome after therapy for localized prostate cancer. DR has been found to occur in up to 53% of patients treated for localized prostate cancer, and it may vary depending on treatment modality. DR after modern dose-escalated radiation therapy (DE-RT) has not been investigated previously, to our knowledge. Our primary aim was to evaluate DR in a cohort of patients treated with DE-RT. Methods and Materials: We surveyed 257 consecutive patients with localized prostate cancer who had previously received DE-RT, by means of a validated questionnaire. Results: There were 220 responses (85.6% response rate). Image-guided intensity modulated radiation therapy was given in 85.0% of patients and 3-dimensional conformal radiation therapy in 15.0%. Doses received included 73.8 Gy (34.5% patients), 74 Gy (53.6%), and 76 Gy (10.9%). Neoadjuvant androgen deprivation (AD) was given in 51.8% of patients and both neoadjuvant and adjuvant AD in 34.5%. The median follow-up time was 23 months (range, 12-67 months). In all, 3.8% of patients expressed DR for their choice of treatment. When asked whether they would choose DE-RT or AD again, only 0.5% probably or definitely would not choose DE-RT again, compared with 8.4% for AD (P<.01). Conclusion: Few patients treated with modern DE-RT express DR, with regret appearing to be lower than in previously published reports of patients treated with radical prostatectomy or older radiation therapy techniques. Patients experienced more regret with the AD component of treatment than with the radiation therapy component, with implications for informed consent. Further research should investigate regret associated with individual components of modern therapy, including AD, radiation therapy and surgery

Decision Regret in Men Undergoing Dose-Escalated Radiation Therapy for Prostate Cancer

Energy Technology Data Exchange (ETDEWEB)

Steer, Anna N. [Department of Radiation Oncology, North Coast Cancer Institute, Coffs Harbour (Australia); Aherne, Noel J., E-mail: noel.aherne@ncahs.health.nsw.gov.au [Department of Radiation Oncology, North Coast Cancer Institute, Coffs Harbour (Australia); Rural Clinical School Faculty of Medicine, University of New South Wales, Coffs Harbour (Australia); Gorzynska, Karen; Hoffman, Matthew; Last, Andrew; Hill, Jacques [Department of Radiation Oncology, North Coast Cancer Institute, Coffs Harbour (Australia); Shakespeare, Thomas P. [Department of Radiation Oncology, North Coast Cancer Institute, Coffs Harbour (Australia); Rural Clinical School Faculty of Medicine, University of New South Wales, Coffs Harbour (Australia)

2013-07-15

Purpose: Decision regret (DR) is a negative emotion associated with medical treatment decisions, and it is an important patient-centered outcome after therapy for localized prostate cancer. DR has been found to occur in up to 53% of patients treated for localized prostate cancer, and it may vary depending on treatment modality. DR after modern dose-escalated radiation therapy (DE-RT) has not been investigated previously, to our knowledge. Our primary aim was to evaluate DR in a cohort of patients treated with DE-RT. Methods and Materials: We surveyed 257 consecutive patients with localized prostate cancer who had previously received DE-RT, by means of a validated questionnaire. Results: There were 220 responses (85.6% response rate). Image-guided intensity modulated radiation therapy was given in 85.0% of patients and 3-dimensional conformal radiation therapy in 15.0%. Doses received included 73.8 Gy (34.5% patients), 74 Gy (53.6%), and 76 Gy (10.9%). Neoadjuvant androgen deprivation (AD) was given in 51.8% of patients and both neoadjuvant and adjuvant AD in 34.5%. The median follow-up time was 23 months (range, 12-67 months). In all, 3.8% of patients expressed DR for their choice of treatment. When asked whether they would choose DE-RT or AD again, only 0.5% probably or definitely would not choose DE-RT again, compared with 8.4% for AD (P<.01). Conclusion: Few patients treated with modern DE-RT express DR, with regret appearing to be lower than in previously published reports of patients treated with radical prostatectomy or older radiation therapy techniques. Patients experienced more regret with the AD component of treatment than with the radiation therapy component, with implications for informed consent. Further research should investigate regret associated with individual components of modern therapy, including AD, radiation therapy and surgery.

Neyman, Markov processes and survival analysis.

Science.gov (United States)

Yang, Grace

2013-07-01

J. Neyman used stochastic processes extensively in his applied work. One example is the Fix and Neyman (F-N) competing risks model (1951) that uses finite homogeneous Markov processes to analyse clinical trials with breast cancer patients. We revisit the F-N model, and compare it with the Kaplan-Meier (K-M) formulation for right censored data. The comparison offers a way to generalize the K-M formulation to include risks of recovery and relapses in the calculation of a patient's survival probability. The generalization is to extend the F-N model to a nonhomogeneous Markov process. Closed-form solutions of the survival probability are available in special cases of the nonhomogeneous processes, like the popular multiple decrement model (including the K-M model) and Chiang's staging model, but these models do not consider recovery and relapses while the F-N model does. An analysis of sero-epidemiology current status data with recurrent events is illustrated. Fix and Neyman used Neyman's RBAN (regular best asymptotic normal) estimates for the risks, and provided a numerical example showing the importance of considering both the survival probability and the length of time of a patient living a normal life in the evaluation of clinical trials. The said extension would result in a complicated model and it is unlikely to find analytical closed-form solutions for survival analysis. With ever increasing computing power, numerical methods offer a viable way of investigating the problem.

The Demographics and Rates of Tattoo Complications, Regret, and Unsafe Tattooing Practices: A Cross-Sectional Study.

Science.gov (United States)

Liszewski, Walter; Kream, Elizabeth; Helland, Sarah; Cavigli, Amy; Lavin, Bridget C; Murina, Andrea

2015-11-01

Tattoos have become increasingly common in the United States; however, there are limited data on the rates of tattoo complications and tattoo regret. To determine the rates of infectious and allergic complications after tattooing, rates of tattoo regret, the perception of dermatologists among people with tattoos, and the demographics of people with tattoos. An 18-question cross-sectional survey was fielded in New Orleans in January 2015. Participants had to be at least 18 years old, have at least 1 tattoo, and reside within the United States. In total, 501 participants from 38 American states were enrolled. Of all participants, 3.2% had a history of an infected tattoo, 3.8% had a history of a painful tattoo, and 21.2% had a history of a pruritic tattoo; 16.2% of participants regret a current tattoo and 21.2% are interested in having 1 or more tattoos removed; 21.2% received a tattoo while intoxicated and 17.6% had a tattoo placed somewhere other than at a tattoo parlor; and 78.9% believe dermatologists are knowledgeable about the infectious and allergic complications of tattoos. Given the rates of pruritic tattoos and tattoo regret, there is an opportunity, and trust among people with tattoos, for dermatologists to manage these complications.

Creating a Next-Generation System of K-12 English Learner Language Proficiency Assessments. Research Report. ETS RR-16-06

Science.gov (United States)

Hauck, Maurice Cogan; Wolf, Mikyung Kim; Mislevy, Robert

2016-01-01

This paper is the first in a series from Educational Testing Service (ETS) concerning English language proficiency (ELP) assessments for K-12 English learners (ELs). The goal of this paper, and the series, is to present research-based ideas, principles, and recommendations for consideration by those who are conceptualizing, developing, and…

Semi-Markov Chains and Hidden Semi-Markov Models toward Applications Their Use in Reliability and DNA Analysis

CERN Document Server

Barbu, Vlad

2008-01-01

Semi-Markov processes are much more general and better adapted to applications than the Markov ones because sojourn times in any state can be arbitrarily distributed, as opposed to the geometrically distributed sojourn time in the Markov case. This book concerns with the estimation of discrete-time semi-Markov and hidden semi-Markov processes

Reliability analysis of Markov history-dependent repairable systems with neglected failures

International Nuclear Information System (INIS)

Du, Shijia; Zeng, Zhiguo; Cui, Lirong; Kang, Rui

2017-01-01

Markov history-dependent repairable systems refer to the Markov repairable systems in which some states are changeable and dependent on recent evolutional history of the system. In practice, many Markov history-dependent repairable systems are subjected to neglected failures, i.e., some failures do not affect system performances if they can be repaired promptly. In this paper, we develop a model based on the theory of aggregated stochastic processes to describe the history-dependent behavior and the effect of neglected failures on the Markov history-dependent repairable systems. Based on the developed model, instantaneous and steady-state availabilities are derived to characterize the reliability of the system. Four reliability-related time distributions, i.e., distribution for the k th working period, distribution for the k th failure period, distribution for the real working time in an effective working period, distribution for the neglected failure time in an effective working period, are also derived to provide a more comprehensive description of the system's reliability. Thanks to the power of the theory of aggregated stochastic processes, closed-form expressions are obtained for all the reliability indexes and time distributions. Finally, the developed indexes and analysis methods are demonstrated by a numerical example. - Highlights: • Markovian history-dependent repairable systems with neglected failures is modeled. • Aggregated stochastic processes are used to derive reliability indexes and time distributions. • Closed-form expressions are derived for the considered indexes and distributions.

Effective instruction for English learners.

Science.gov (United States)

Calderón, Margarita; Slavin, Robert; Sánchez, Marta

2011-01-01

The fastest-growing student population in U.S. schools today is children of immigrants, half of whom do not speak English fluently and are thus labeled English learners. Although the federal government requires school districts to provide services to English learners, it offers states no policies to follow in identifying, assessing, placing, or instructing them. Margarita Calderón, Robert Slavin, and Marta Sánchez identify the elements of effective instruction and review a variety of successful program models. During 2007-08, more than 5.3 million English learners made up 10.6 percent of the nation's K-12 public school enrollment. Wide and persistent achievement disparities between these English learners and English-proficient students show clearly, say the authors, that schools must address the language, literacy, and academic needs of English learners more effectively. Researchers have fiercely debated the merits of bilingual and English-only reading instruction. In elementary schools, English learners commonly receive thirty minutes of English as a Second Language (ESL) instruction but attend general education classes for the rest of the day, usually with teachers who are unprepared to teach them. Though English learners have strikingly diverse levels of skills, in high school they are typically lumped together, with one teacher to address their widely varying needs. These in-school factors contribute to the achievement disparities. Based on the studies presented here, Calderón, Slavin, and Sánchez assert that the quality of instruction is what matters most in educating English learners. They highlight comprehensive reform models, as well as individual components of these models: school structures and leadership; language and literacy instruction; integration of language, literacy, and content instruction in secondary schools; cooperative learning; professional development; parent and family support teams; tutoring; and monitoring implementation and outcomes

Phasic Triplet Markov Chains.

Science.gov (United States)

El Yazid Boudaren, Mohamed; Monfrini, Emmanuel; Pieczynski, Wojciech; Aïssani, Amar

2014-11-01

Hidden Markov chains have been shown to be inadequate for data modeling under some complex conditions. In this work, we address the problem of statistical modeling of phenomena involving two heterogeneous system states. Such phenomena may arise in biology or communications, among other fields. Namely, we consider that a sequence of meaningful words is to be searched within a whole observation that also contains arbitrary one-by-one symbols. Moreover, a word may be interrupted at some site to be carried on later. Applying plain hidden Markov chains to such data, while ignoring their specificity, yields unsatisfactory results. The Phasic triplet Markov chain, proposed in this paper, overcomes this difficulty by means of an auxiliary underlying process in accordance with the triplet Markov chains theory. Related Bayesian restoration techniques and parameters estimation procedures according to the new model are then described. Finally, to assess the performance of the proposed model against the conventional hidden Markov chain model, experiments are conducted on synthetic and real data.

Non-stationary Markov chains

OpenAIRE

Mallak, Saed

1996-01-01

Ankara : Department of Mathematics and Institute of Engineering and Sciences of Bilkent University, 1996. Thesis (Master's) -- Bilkent University, 1996. Includes bibliographical references leaves leaf 29 In thi.s work, we studierl the Ergodicilv of Non-Stationary .Markov chains. We gave several e.xainples with different cases. We proved that given a sec[uence of Markov chains such that the limit of this sec|uence is an Ergodic Markov chain, then the limit of the combination ...

Process Algebra and Markov Chains

NARCIS (Netherlands)

Brinksma, Hendrik; Hermanns, H.; Brinksma, Hendrik; Hermanns, H.; Katoen, Joost P.

This paper surveys and relates the basic concepts of process algebra and the modelling of continuous time Markov chains. It provides basic introductions to both fields, where we also study the Markov chains from an algebraic perspective, viz. that of Markov chain algebra. We then proceed to study

Process algebra and Markov chains

NARCIS (Netherlands)

Brinksma, E.; Hermanns, H.; Brinksma, E.; Hermanns, H.; Katoen, J.P.

2001-01-01

This paper surveys and relates the basic concepts of process algebra and the modelling of continuous time Markov chains. It provides basic introductions to both fields, where we also study the Markov chains from an algebraic perspective, viz. that of Markov chain algebra. We then proceed to study

Criterion of Semi-Markov Dependent Risk Model

Institute of Scientific and Technical Information of China (English)

Xiao Yun MO; Xiang Qun YANG

2014-01-01

A rigorous definition of semi-Markov dependent risk model is given. This model is a generalization of the Markov dependent risk model. A criterion and necessary conditions of semi-Markov dependent risk model are obtained. The results clarify relations between elements among semi-Markov dependent risk model more clear and are applicable for Markov dependent risk model.

Transparency systems: do businesses in North Rhine-Westphalia (Germany regret the cancellation of the Smiley scheme?

Directory of Open Access Journals (Sweden)

Anica Veronika Fietz

2017-11-01

Full Text Available Abstract Our paper explores how participants of voluntary transparency systems react to the cancellation of such programmes. We concern ourselves with participants of the voluntary transparency scheme known as the “North Rhine-Westphalia Smiley”. The Smiley system, which awarded the compliant behavior of businesses that joined it, was established in 2007 but cancelled in 2013 due to lack of participants. In our survey, the vast majority of the respondents express regret at the cancellation of the scheme. The goals of this paper are to (i econometrically explain how socio-demographic, monetary, and non-monetary determinants influence participants’ willingness to continue with the voluntary transparency system and (ii find reasons for the inconsistency between the lack of participants and the expression of regret within our survey. We find evidence that the non-monetary variables “revenue” and “award” and the monetary variable “revenue” influence participants’ regret. We speculate that status quo bias and loss aversion are the reasons why businesses favour maintaining the Smiley scheme once they have experienced it.

Markov chains of nonlinear Markov processes and an application to a winner-takes-all model for social conformity

Energy Technology Data Exchange (ETDEWEB)

Frank, T D [Center for the Ecological Study of Perception and Action, Department of Psychology, University of Connecticut, 406 Babbidge Road, Storrs, CT 06269 (United States)

2008-07-18

We discuss nonlinear Markov processes defined on discrete time points and discrete state spaces using Markov chains. In this context, special attention is paid to the distinction between linear and nonlinear Markov processes. We illustrate that the Chapman-Kolmogorov equation holds for nonlinear Markov processes by a winner-takes-all model for social conformity. (fast track communication)

Markov chains of nonlinear Markov processes and an application to a winner-takes-all model for social conformity

International Nuclear Information System (INIS)

Frank, T D

2008-01-01

We discuss nonlinear Markov processes defined on discrete time points and discrete state spaces using Markov chains. In this context, special attention is paid to the distinction between linear and nonlinear Markov processes. We illustrate that the Chapman-Kolmogorov equation holds for nonlinear Markov processes by a winner-takes-all model for social conformity. (fast track communication)

Geometry and Dynamics for Markov Chain Monte Carlo

Science.gov (United States)

Barp, Alessandro; Briol, François-Xavier; Kennedy, Anthony D.; Girolami, Mark

2018-03-01

Markov Chain Monte Carlo methods have revolutionised mathematical computation and enabled statistical inference within many previously intractable models. In this context, Hamiltonian dynamics have been proposed as an efficient way of building chains which can explore probability densities efficiently. The method emerges from physics and geometry and these links have been extensively studied by a series of authors through the last thirty years. However, there is currently a gap between the intuitions and knowledge of users of the methodology and our deep understanding of these theoretical foundations. The aim of this review is to provide a comprehensive introduction to the geometric tools used in Hamiltonian Monte Carlo at a level accessible to statisticians, machine learners and other users of the methodology with only a basic understanding of Monte Carlo methods. This will be complemented with some discussion of the most recent advances in the field which we believe will become increasingly relevant to applied scientists.

No-regrets, efficiency improvements and penetration rates for end-use technologies

International Nuclear Information System (INIS)

Morthorst, P.E.

1995-01-01

Denmark participated in the UNEP Greenhouse Gas Abatement Costing Study which was aimed at developing a common methodology for undertaking cost assessments of greenhouse gas abatement, and using this methodology to carry out a number of country studies. One of the main components of the Danish country study was the methodological analysis of cost curve construction and the testing of the developed methodology on national CO 2 reduction scenarios. Following the development of a baseline scenario, two main reduction scenarios were constructed: (a) a 20% reduction scenario for 2005, and (b) a 50% reduction scenario for 2030, taking as its starting point the 20% scenario for 2005. The medium-term cost curve for 2005 and long-term cost curve for 2030 for CO 2 reduction were established on the basis of these two reduction scenarios. The existence of so-called 'no-regret' options are discussed. No-regret options exist when it is economically attractive for society to undertake these options and at the same time reduce CO 2 -emissions. Two illustrative cases are developed describing the introduction of standards for households appliances. It is shown that introduction of such standards for household appliances might be an attractive way to accelerate the adjustment process towards more efficient appliances. Improving standards for household appliances could reduce CO-2-emissions in 2005 by approximately 2% compared to the baseline, and at the same time lower the energy-system cost to society. Three-quarters of the CO 2 emission reductions are realized through supply-side options. Restricting the use of no-regret demand-side options would require additional supply-side CO 2 reduction in order to achieve the same reduction target, and this might prove very difficult to achieve. (au)

Flux through a Markov chain

International Nuclear Information System (INIS)

Floriani, Elena; Lima, Ricardo; Ourrad, Ouerdia; Spinelli, Lionel

2016-01-01

Highlights: • The flux through a Markov chain of a conserved quantity (mass) is studied. • Mass is supplied by an external source and ends in the absorbing states of the chain. • Meaningful for modeling open systems whose dynamics has a Markov property. • The analytical expression of mass distribution is given for a constant source. • The expression of mass distribution is given for periodic or random sources. - Abstract: In this paper we study the flux through a finite Markov chain of a quantity, that we will call mass, which moves through the states of the chain according to the Markov transition probabilities. Mass is supplied by an external source and accumulates in the absorbing states of the chain. We believe that studying how this conserved quantity evolves through the transient (non-absorbing) states of the chain could be useful for the modelization of open systems whose dynamics has a Markov property.

The potential role of regret in the physician-patient relationship: insights from neuroeconomics.

Science.gov (United States)

Coricelli, Giorgio

2008-01-01

The aim of the chapter is to show how two important facts of physicians' behavior, (i) their tendency to "create" the demand for medical practices, and (ii) their delay and reluctance in using new treatments and therapies, can be explained with the lens of the neuroeconomics research on the neural and behavioral basis of regret. This chapter adopts a neuroeconomics perspective on decision-making, asking how the brain represents values and generates emotional states, which consequently influence choices. In the line of recent work on emotion-based decision-making, we expect to be able to characterize the brain areas underlying the studied processes and to specify the functional relationship between rational decision-making and the emotional influences that modulate these decisional processes. Neurobiological approaches can contribute significantly to a better understanding of the cognitive and emotional underpinnings of medical decision-making, from how physicians might evaluate and anticipate the effect of alternative therapies, to how patients might anticipate future consequences of their health choice. This can explain some features of the doctor-patient relationship which are not consistent with simple maximization models. Our findings suggest that physicians' behavior can be often explained by regret avoidance. Likewise, they suggest that physicians play as actual agents when they make medical decisions that will affect the future well-being of their patients. We limited our analysis to the potential role of anticipated regret; therefore, this chapter neglects many important factors of the health sector.

Semi-Markov Arnason-Schwarz models.

Science.gov (United States)

King, Ruth; Langrock, Roland

2016-06-01

We consider multi-state capture-recapture-recovery data where observed individuals are recorded in a set of possible discrete states. Traditionally, the Arnason-Schwarz model has been fitted to such data where the state process is modeled as a first-order Markov chain, though second-order models have also been proposed and fitted to data. However, low-order Markov models may not accurately represent the underlying biology. For example, specifying a (time-independent) first-order Markov process involves the assumption that the dwell time in each state (i.e., the duration of a stay in a given state) has a geometric distribution, and hence that the modal dwell time is one. Specifying time-dependent or higher-order processes provides additional flexibility, but at the expense of a potentially significant number of additional model parameters. We extend the Arnason-Schwarz model by specifying a semi-Markov model for the state process, where the dwell-time distribution is specified more generally, using, for example, a shifted Poisson or negative binomial distribution. A state expansion technique is applied in order to represent the resulting semi-Markov Arnason-Schwarz model in terms of a simpler and computationally tractable hidden Markov model. Semi-Markov Arnason-Schwarz models come with only a very modest increase in the number of parameters, yet permit a significantly more flexible state process. Model selection can be performed using standard procedures, and in particular via the use of information criteria. The semi-Markov approach allows for important biological inference to be drawn on the underlying state process, for example, on the times spent in the different states. The feasibility of the approach is demonstrated in a simulation study, before being applied to real data corresponding to house finches where the states correspond to the presence or absence of conjunctivitis. © 2015, The International Biometric Society.

Impact of CAre-related Regret Upon Sleep (ICARUS) cohort study: protocol of a 3-year multicentre, international, prospective cohort study of novice healthcare professionals.

Science.gov (United States)

Cheval, Boris; Cullati, Stéphane; Pihl-Thingvad, Jesper; Mongin, Denis; Von Arx, Martina; Chopard, Pierre; Courvoisier, Delphine S

2018-03-27

Healthcare professionals are particularly at risk of developing numerous physical and psychological health problems. The experiences of emotional burden associated with providing healthcare, notably care-related regret, have been associated with these health problems, but only using cross-sectional data so far. Evidence of a causal impact of regret has not been assessed. The Impact of CAre-related Regret Upon Sleep (ICARUS) study is the first prospective and international cohort study established to examine how newly practising healthcare professionals adapt to their challenging job by assessing the impact of care-related regret on sleep and job quitting. The ICARUS cohort study will include newly practising healthcare professionals working in acute care hospitals and clinics recruited between May 2017 and November 2019. Data collection, which will begin as soon as the participant starts working with patients, will consist of a 1-year weekly assessment using a secure web survey. Follow-up data will be collected at 6, 12, 18 and 24 months after the end of the first year. We will collect detailed information on the experience of care-related regret (ie, highest regret intensity, accumulation of regrets and coping strategies related to regrets), sleep problems and job quitting. Moreover, quality of life, health status and burnout will be assessed during the follow-up. Several confounders factors, including sociodemographic characteristics, personality, night shifts and work environment characteristics, will be assessed. The study was approved by the Ethics Committee of Geneva Canton, Switzerland (CCER2016-02041), the Ethics Committee of London South Bank University (HSCSEP/17/06) and the University Research Ethics Committee of Bedfordshire (UREC106). Other study centres deemed local ethical approval unnecessary since the main ethics committee (Geneva) had already accepted the project. Results will be published in relevant scientific journals and be disseminated in

Utilization of two web-based continuing education courses evaluated by Markov chain model.

Science.gov (United States)

Tian, Hao; Lin, Jin-Mann S; Reeves, William C

2012-01-01

To evaluate the web structure of two web-based continuing education courses, identify problems and assess the effects of web site modifications. Markov chain models were built from 2008 web usage data to evaluate the courses' web structure and navigation patterns. The web site was then modified to resolve identified design issues and the improvement in user activity over the subsequent 12 months was quantitatively evaluated. Web navigation paths were collected between 2008 and 2010. The probability of navigating from one web page to another was analyzed. The continuing education courses' sequential structure design was clearly reflected in the resulting actual web usage models, and none of the skip transitions provided was heavily used. The web navigation patterns of the two different continuing education courses were similar. Two possible design flaws were identified and fixed in only one of the two courses. Over the following 12 months, the drop-out rate in the modified course significantly decreased from 41% to 35%, but remained unchanged in the unmodified course. The web improvement effects were further verified via a second-order Markov chain model. The results imply that differences in web content have less impact than web structure design on how learners navigate through continuing education courses. Evaluation of user navigation can help identify web design flaws and guide modifications. This study showed that Markov chain models provide a valuable tool to evaluate web-based education courses. Both the results and techniques in this study would be very useful for public health education and research specialists.

Markov Tail Chains

OpenAIRE

janssen, Anja; Segers, Johan

2013-01-01

The extremes of a univariate Markov chain with regularly varying stationary marginal distribution and asymptotically linear behavior are known to exhibit a multiplicative random walk structure called the tail chain. In this paper we extend this fact to Markov chains with multivariate regularly varying marginal distributions in Rd. We analyze both the forward and the backward tail process and show that they mutually determine each other through a kind of adjoint relation. In ...

Decision conflict and regret among surrogate decision makers in the medical intensive care unit.

Science.gov (United States)

Miller, Jesse J; Morris, Peter; Files, D Clark; Gower, Emily; Young, Michael

2016-04-01

Family members of critically ill patients in the intensive care unit face significant morbidity. It may be the decision-making process that plays a significant role in the psychological morbidity associated with being a surrogate in the ICU. We hypothesize that family members facing end-of-life decisions will have more decisional conflict and decisional regret than those facing non-end-of-life decisions. We enrolled a sample of adult patients and their surrogates in a tertiary care, academic medical intensive care unit. We queried the surrogates regarding decisions they had made on behalf of the patient and assessed decision conflict. We then contacted the family member again to assess decision regret. Forty (95%) of 42 surrogates were able to identify at least 1 decision they had made on behalf of the patient. End-of-life decisions (defined as do not resuscitate [DNR]/do not intubate [DNI] or continuation of life support) accounted for 19 of 40 decisions (47.5%). Overall, the average Decision Conflict Scale (DCS) score was 21.9 of 100 (range 0-100, with 0 being little decisional conflict and 100 being great decisional conflict). The average DCS score for families facing end-of-life decisions was 25.5 compared with 18.7 for all other decisions. Those facing end-of-life decisions scored higher on the uncertainty subscale (subset of DCS questions that indicates level of certainty regarding decision) with a mean score of 43.4 compared with all other decisions with a mean score of 27.0. Overall, very few surrogates experienced decisional regret with an average DRS score of 13.4 of 100. Nearly all surrogates enrolled were faced with decision-making responsibilities on behalf of his or her critically ill family member. In our small pilot study, we found more decisional conflict in those surrogates facing end-of-life decisions, specifically on the subset of questions dealing with uncertainty. Surrogates report low levels of decisional regret. Copyright © 2015 Elsevier

Reviving Markov processes and applications

International Nuclear Information System (INIS)

Cai, H.

1988-01-01

In this dissertation we study a procedure which restarts a Markov process when the process is killed by some arbitrary multiplicative functional. The regenerative nature of this revival procedure is characterized through a Markov renewal equation. An interesting duality between the revival procedure and the classical killing operation is found. Under the condition that the multiplicative functional possesses an intensity, the generators of the revival process can be written down explicitly. An intimate connection is also found between the perturbation of the sample path of a Markov process and the perturbation of a generator (in Kato's sense). The applications of the theory include the study of the processes like piecewise-deterministic Markov process, virtual waiting time process and the first entrance decomposition (taboo probability)

[Compared Markov with fractal models by using single-channel experimental and simulation data].

Science.gov (United States)

Lan, Tonghan; Wu, Hongxiu; Lin, Jiarui

2006-10-01

The gating mechanical kinetical of ion channels has been modeled as a Markov process. In these models it is assumed that the channel protein has a small number of discrete conformational states and kinetic rate constants connecting these states are constant, the transition rate constants among the states is independent both of time and of the previous channel activity. It is assumed in Liebovitch's fractal model that the channel exists in an infinite number of energy states, consequently, transitions from one conductance state to another would be governed by a continuum of rate constants. In this paper, a statistical comparison is presented of Markov and fractal models of ion channel gating, the analysis is based on single-channel data from ion channel voltage-dependence K+ single channel of neuron cell and simulation data from three-states Markov model.

Random regret and random utility in the household purchase of a motor vehicle

NARCIS (Netherlands)

Beck, M.; Chorus, C.G.; Rose, J.M.; Hensher, D.A.

2013-01-01

Random utility maximisation is the preeminent behavioural theory used to model choices. An alternative paradigm, however, is random regret minimisation. While the majority of the literature examines the choices of individuals, this paper compares the choices of groups, as well individuals, in both

Arrependimento após a esterilização feminina no Brasil Regret subsequent to sterilization among Brazilian women

Directory of Open Access Journals (Sweden)

Luciana Freitas Barbosa

2009-06-01

Full Text Available OBJETIVOS: identificar fatores sócio-demográficos associados com o arrependimento após a esterilização. MÉTODOS: trata-se de um estudo de corte transversal com dados da Pesquisa Nacional de Demografia e Saúde realizada no Brasil em 1996. A amostra é composta por 3233 mulheres em idade reprodutiva, cuja esterilização ocorreu há pelo menos um ano antes da entrevista. Um modelo de regressão logística foi utilizado. RESULTADOS: a proporção de mulheres arrependidas foi de 10,5% e a principal razão relatada foi o desejo de ter outro filho (62,7%. A chance de uma mulher esterilizada com 35 anos ou mais se arrepender é 69% menor que uma mulher com menos de 25 anos (pOBJECTIVES: to identify socio-demographic factors associated with regret following sterilization. METHODS: a cross-cutting study was carried out using data from the National Population and Health Survey conducted in Brazil in 1996. The sample comprised 3233 women of child-bearing age who had been sterilized at least one year prior to the interview. The logistic regression model was employed. RESULTS: the proportion of women regretting sterilization was 10.5% and the main reason reported was the desire to have another child (62.7%. The likelihood of a sterilized woman aged 35 years or over regretting sterilization was less than that for women aged below 25 years (p<0.01. Women with more than nine years of schooling are less likely to regret sterilization than women with three years of schooling or less (RC=0.75; 95%CI: 0.51-1.03. CONCLUSIONS: young women with a low level of education are the group that is most likely to have regrets following sterilization. These results may aid family planning program managers, restating the need for orientation regarding the irreversibility of the method and the changes that may occur in the lives of women in the course of the reproductive cycle, thereby minimizing the possibility of a woman coming to regret the decision.

Performance Modeling of Communication Networks with Markov Chains

CERN Document Server

Mo, Jeonghoon

2010-01-01

This book is an introduction to Markov chain modeling with applications to communication networks. It begins with a general introduction to performance modeling in Chapter 1 where we introduce different performance models. We then introduce basic ideas of Markov chain modeling: Markov property, discrete time Markov chain (DTMe and continuous time Markov chain (CTMe. We also discuss how to find the steady state distributions from these Markov chains and how they can be used to compute the system performance metric. The solution methodologies include a balance equation technique, limiting probab

Fields From Markov Chains

DEFF Research Database (Denmark)

Justesen, Jørn

2005-01-01

A simple construction of two-dimensional (2-D) fields is presented. Rows and columns are outcomes of the same Markov chain. The entropy can be calculated explicitly.......A simple construction of two-dimensional (2-D) fields is presented. Rows and columns are outcomes of the same Markov chain. The entropy can be calculated explicitly....

Regret in repeat purchase versus switching decisions : The attenuating role of decision justifiability

NARCIS (Netherlands)

Inman, J.J.; Zeelenberg, M.

2002-01-01

The decision-making literature has consistently reported that decisions to maintain the status quo tend to be regretted less than decisions to change it. We examine the consequences of repeat purchasing (maintaining the status quo) versus switching in the context of information regarding the reason

Regeneration and general Markov chains

Directory of Open Access Journals (Sweden)

Vladimir V. Kalashnikov

1994-01-01

Full Text Available Ergodicity, continuity, finite approximations and rare visits of general Markov chains are investigated. The obtained results permit further quantitative analysis of characteristics, such as, rates of convergence, continuity (measured as a distance between perturbed and non-perturbed characteristics, deviations between Markov chains, accuracy of approximations and bounds on the distribution function of the first visit time to a chosen subset, etc. The underlying techniques use the embedding of the general Markov chain into a wide sense regenerative process with the help of splitting construction.

Markov set-chains

CERN Document Server

Hartfiel, Darald J

1998-01-01

In this study extending classical Markov chain theory to handle fluctuating transition matrices, the author develops a theory of Markov set-chains and provides numerous examples showing how that theory can be applied. Chapters are concluded with a discussion of related research. Readers who can benefit from this monograph are those interested in, or involved with, systems whose data is imprecise or that fluctuate with time. A background equivalent to a course in linear algebra and one in probability theory should be sufficient.

Markov chains theory and applications

CERN Document Server

Sericola, Bruno

2013-01-01

Markov chains are a fundamental class of stochastic processes. They are widely used to solve problems in a large number of domains such as operational research, computer science, communication networks and manufacturing systems. The success of Markov chains is mainly due to their simplicity of use, the large number of available theoretical results and the quality of algorithms developed for the numerical evaluation of many metrics of interest.The author presents the theory of both discrete-time and continuous-time homogeneous Markov chains. He carefully examines the explosion phenomenon, the

Quadratic Variation by Markov Chains

DEFF Research Database (Denmark)

Hansen, Peter Reinhard; Horel, Guillaume

We introduce a novel estimator of the quadratic variation that is based on the the- ory of Markov chains. The estimator is motivated by some general results concerning filtering contaminated semimartingales. Specifically, we show that filtering can in prin- ciple remove the effects of market...... microstructure noise in a general framework where little is assumed about the noise. For the practical implementation, we adopt the dis- crete Markov chain model that is well suited for the analysis of financial high-frequency prices. The Markov chain framework facilitates simple expressions and elegant analyti...

Confluence reduction for Markov automata

NARCIS (Netherlands)

Timmer, Mark; Katoen, Joost P.; van de Pol, Jaco; Stoelinga, Mariëlle Ida Antoinette

2016-01-01

Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. As expected, the state space explosion threatens the analysability of these models. We therefore introduce confluence reduction for Markov automata, a powerful reduction

Colour and rotation invariant textural features based on Markov random fields

Czech Academy of Sciences Publication Activity Database

Vácha, Pavel; Haindl, Michal; Suk, Tomáš

2011-01-01

Roč. 32, č. 6 (2011), s. 771-779 ISSN 0167-8655 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Image modelling * colour texture * Illumination invariance * Markov random field * rotation invariance Subject RIV: BD - Theory of Information Impact factor: 1.034, year: 2011 http://library.utia.cas.cz/separaty/2011/RO/vacha-0357314.pdf

Heuristic algorithms for the minmax regret flow-shop problem with interval processing times.

Science.gov (United States)

Ćwik, Michał; Józefczyk, Jerzy

2018-01-01

An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations are applied to simplify the optimization procedure. First of all, a greedy procedure is used for calculating the criterion's value, as such calculation is NP-hard problem itself. Moreover, the lower bound is used instead of solving the internal deterministic flow-shop. The constructive heuristic algorithm is applied for the relaxed optimization problem. The algorithm is compared with previously elaborated other heuristic algorithms basing on the evolutionary and the middle interval approaches. The conducted computational experiments showed the advantage of the constructive heuristic algorithm with regards to both the criterion and the time of computations. The Wilcoxon paired-rank statistical test confirmed this conclusion.

Verification of Open Interactive Markov Chains

OpenAIRE

Brazdil, Tomas; Hermanns, Holger; Krcal, Jan; Kretinsky, Jan; Rehak, Vojtech

2012-01-01

Interactive Markov chains (IMC) are compositional behavioral models extending both labeled transition systems and continuous-time Markov chains. IMC pair modeling convenience - owed to compositionality properties - with effective verification algorithms and tools - owed to Markov properties. Thus far however, IMC verification did not consider compositionality properties, but considered closed systems. This paper discusses the evaluation of IMC in an open and thus compositional interpretation....

Regulating emotion in the context of interpersonal decisions: The role of anticipated pride and regret

Directory of Open Access Journals (Sweden)

Job eVan Der Schalk

2012-11-01

Full Text Available Recent theories about the relation between emotion and behavior hold that social behavior is influenced not only by the experience of emotion, but also by the anticipation of emotion. We argue that anticipating future emotional states is an emotion regulation strategy when it leads to a change in behavior. In the current studies we examined how construal of a fair or an unfair situation in terms of positive or negative anticipated emotions influences the fairness of subsequent behavior. We used the Ultimatum Bargaining Game--an experimental game in which participants divide a resource between themselves and another person--as a social situation that offers the opportunity to engage in fair and unfair behavior. In Study 1 we used an autobiographical recall task to manipulate anticipated emotions. Although the task did not influence anticipated emotions directly, results showed that anticipated pride about fair behavior increased levels of fairness, whereas anticipated pride about unfair behavior decreased levels of fairness. Similarly, anticipated regret about fair behavior decreased levels of fairness, whereas anticipated regret about unfair behavior increased levels of fairness. In Study 2 we replicated this pattern of findings, and found that participants who thought about their anticipated emotions (pride or regret in relation to unfair behavior behaved more fairly. We discuss these findings in relation to theories of emotion regulation and economic decision-making.

Classification Using Markov Blanket for Feature Selection

DEFF Research Database (Denmark)

Zeng, Yifeng; Luo, Jian

2009-01-01

Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

Consistency and refinement for Interval Markov Chains

DEFF Research Database (Denmark)

Delahaye, Benoit; Larsen, Kim Guldstrand; Legay, Axel

2012-01-01

Interval Markov Chains (IMC), or Markov Chains with probability intervals in the transition matrix, are the base of a classic specification theory for probabilistic systems [18]. The standard semantics of IMCs assigns to a specification the set of all Markov Chains that satisfy its interval...

Honest Importance Sampling with Multiple Markov Chains.

Science.gov (United States)

Tan, Aixin; Doss, Hani; Hobert, James P

2015-01-01

Importance sampling is a classical Monte Carlo technique in which a random sample from one probability density, π 1 , is used to estimate an expectation with respect to another, π . The importance sampling estimator is strongly consistent and, as long as two simple moment conditions are satisfied, it obeys a central limit theorem (CLT). Moreover, there is a simple consistent estimator for the asymptotic variance in the CLT, which makes for routine computation of standard errors. Importance sampling can also be used in the Markov chain Monte Carlo (MCMC) context. Indeed, if the random sample from π 1 is replaced by a Harris ergodic Markov chain with invariant density π 1 , then the resulting estimator remains strongly consistent. There is a price to be paid however, as the computation of standard errors becomes more complicated. First, the two simple moment conditions that guarantee a CLT in the iid case are not enough in the MCMC context. Second, even when a CLT does hold, the asymptotic variance has a complex form and is difficult to estimate consistently. In this paper, we explain how to use regenerative simulation to overcome these problems. Actually, we consider a more general set up, where we assume that Markov chain samples from several probability densities, π 1 , …, π k , are available. We construct multiple-chain importance sampling estimators for which we obtain a CLT based on regeneration. We show that if the Markov chains converge to their respective target distributions at a geometric rate, then under moment conditions similar to those required in the iid case, the MCMC-based importance sampling estimator obeys a CLT. Furthermore, because the CLT is based on a regenerative process, there is a simple consistent estimator of the asymptotic variance. We illustrate the method with two applications in Bayesian sensitivity analysis. The first concerns one-way random effects models under different priors. The second involves Bayesian variable

Nonlinearly perturbed semi-Markov processes

CERN Document Server

Silvestrov, Dmitrii

2017-01-01

The book presents new methods of asymptotic analysis for nonlinearly perturbed semi-Markov processes with a finite phase space. These methods are based on special time-space screening procedures for sequential phase space reduction of semi-Markov processes combined with the systematical use of operational calculus for Laurent asymptotic expansions. Effective recurrent algorithms are composed for getting asymptotic expansions, without and with explicit upper bounds for remainders, for power moments of hitting times, stationary and conditional quasi-stationary distributions for nonlinearly perturbed semi-Markov processes. These results are illustrated by asymptotic expansions for birth-death-type semi-Markov processes, which play an important role in various applications. The book will be a useful contribution to the continuing intensive studies in the area. It is an essential reference for theoretical and applied researchers in the field of stochastic processes and their applications that will cont...

Nonlinear Markov processes: Deterministic case

International Nuclear Information System (INIS)

Frank, T.D.

2008-01-01

Deterministic Markov processes that exhibit nonlinear transition mechanisms for probability densities are studied. In this context, the following issues are addressed: Markov property, conditional probability densities, propagation of probability densities, multistability in terms of multiple stationary distributions, stability analysis of stationary distributions, and basin of attraction of stationary distribution

Spectral methods for quantum Markov chains

Energy Technology Data Exchange (ETDEWEB)

Szehr, Oleg

2014-05-08

The aim of this project is to contribute to our understanding of quantum time evolutions, whereby we focus on quantum Markov chains. The latter constitute a natural generalization of the ubiquitous concept of a classical Markov chain to describe evolutions of quantum mechanical systems. We contribute to the theory of such processes by introducing novel methods that allow us to relate the eigenvalue spectrum of the transition map to convergence as well as stability properties of the Markov chain.

Spectral methods for quantum Markov chains

International Nuclear Information System (INIS)

Szehr, Oleg

2014-01-01

The aim of this project is to contribute to our understanding of quantum time evolutions, whereby we focus on quantum Markov chains. The latter constitute a natural generalization of the ubiquitous concept of a classical Markov chain to describe evolutions of quantum mechanical systems. We contribute to the theory of such processes by introducing novel methods that allow us to relate the eigenvalue spectrum of the transition map to convergence as well as stability properties of the Markov chain.

A Multilayer Hidden Markov Models-Based Method for Human-Robot Interaction

Directory of Open Access Journals (Sweden)

Chongben Tao

2013-01-01

Full Text Available To achieve Human-Robot Interaction (HRI by using gestures, a continuous gesture recognition approach based on Multilayer Hidden Markov Models (MHMMs is proposed, which consists of two parts. One part is gesture spotting and segment module, the other part is continuous gesture recognition module. Firstly, a Kinect sensor is used to capture 3D acceleration and 3D angular velocity data of hand gestures. And then, a Feed-forward Neural Networks (FNNs and a threshold criterion are used for gesture spotting and segment, respectively. Afterwards, the segmented gesture signals are respectively preprocessed and vector symbolized by a sliding window and a K-means clustering method. Finally, symbolized data are sent into Lower Hidden Markov Models (LHMMs to identify individual gestures, and then, a Bayesian filter with sequential constraints among gestures in Upper Hidden Markov Models (UHMMs is used to correct recognition errors created in LHMMs. Five predefined gestures are used to interact with a Kinect mobile robot in experiments. The experimental results show that the proposed method not only has good effectiveness and accuracy, but also has favorable real-time performance.

Will I regret it? Anticipated negative emotions modulate choices in moral dilemmas

Directory of Open Access Journals (Sweden)

Carolina Pletti

2016-12-01

Full Text Available We tested if post-decisional emotions of regret, guilt, shame, anger, and disgust can account for individuals’ choices in moral dilemmas depicting the choice of letting some people die (non-utilitarian option or sacrificing one person to save them (utilitarian option. We collected participants’ choices and post-decisional emotional ratings for each option using Footbridge-type dilemmas, in which the sacrifice of one person is the means to save more people, and Trolley-type dilemmas, in which the sacrifice is only a side effect. Moreover, we computed the EEG Readiness Potential to test if the neural activity related to the last phase of decision-making was related to the emotional conflict. Participants reported generally stronger emotions for the utilitarian as compared to the non-utilitarian options, with the exception of anger and regret, which in Trolley-type dilemmas were stronger for the non-utilitarian option. Moreover, participants tended to choose the option that minimized the intensity of negative emotions, irrespective of dilemma type. No significant relationship between emotions and the amplitude of the Readiness Potential emerged. It is possible that anticipated post-decisional emotions play a role in earlier stages of decision-making.

Will I Regret It? Anticipated Negative Emotions Modulate Choices in Moral Dilemmas

Science.gov (United States)

Pletti, Carolina; Lotto, Lorella; Tasso, Alessandra; Sarlo, Michela

2016-01-01

We tested if post-decisional emotions of regret, guilt, shame, anger, and disgust can account for individuals’ choices in moral dilemmas depicting the choice of letting some people die (non-utilitarian option) or sacrificing one person to save them (utilitarian option). We collected participants’ choices and post-decisional emotional ratings for each option using Footbridge-type dilemmas, in which the sacrifice of one person is the means to save more people, and Trolley-type dilemmas, in which the sacrifice is only a side effect. Moreover, we computed the EEG Readiness Potential to test if the neural activity related to the last phase of decision-making was related to the emotional conflict. Participants reported generally stronger emotions for the utilitarian as compared to the non-utilitarian options, with the exception of anger and regret, which in Trolley-type dilemmas were stronger for the non-utilitarian option. Moreover, participants tended to choose the option that minimized the intensity of negative emotions, irrespective of dilemma type. No significant relationship between emotions and the amplitude of the Readiness Potential emerged. It is possible that anticipated post-decisional emotions play a role in earlier stages of decision-making. PMID:27999559

Design of Biomass Combined Heat and Power (CHP Systems based on Economic Risk using Minimax Regret Criterion

Directory of Open Access Journals (Sweden)

Ling Wen Choong

2018-01-01

Full Text Available It is a great challenge to identify optimum technologies for CHP systems that utilise biomass and convert it into heat and power. In this respect, industry decision makers are lacking in confidence to invest in biomass CHP due to economic risk from varying energy demand. This research work presents a linear programming systematic framework to design biomass CHP system based on potential loss of profit due to varying energy demand. Minimax Regret Criterion (MRC approach was used to assess maximum regret between selections of the given biomass CHP design based on energy demand. Based on this, the model determined an optimal biomass CHP design with minimum regret in economic opportunity. As Feed-in Tariff (FiT rates affects the revenue of the CHP plant, sensitivity analysis was then performed on FiT rates on the selection of biomass CHP design. Besides, design analysis on the trend of the optimum design selected by model was conducted. To demonstrate the proposed framework in this research, a case study was solved using the proposed approach. The case study focused on designing a biomass CHP system for a palm oil mill (POM due to large energy potential of oil palm biomass in Malaysia.

A longitudinal study investigating the role of decisional conflicts and regret and short-term psychological adjustment after IVF treatment failure.

Science.gov (United States)

Chan, Celia Hoi Yan; Lau, Hi Po Bobo; Tam, Michelle Yi Jun; Ng, Ernest Hung Yu

2016-12-01

What is the relationship between decisional conflict, decisional regret and psychological well-being in women following unsuccessful IVF cycles? The mediating effect of decisional regret on the relationship between decisional conflict and fertility-related quality of life (FRQOL) has been found to be moderated by the availability (versus absence) of frozen embryos after an unsuccessful IVF cycle. Infertility treatment is marked by its open-ended nature. Stresses in treatment decision-making could be aggravated by a culture which honours families through procreation. While studies have investigated treatment-related decision-making among infertile women, little is known about the mental health consequences of decisional conflict and decisional regret following an unsuccessful IVF cycle. A study was conducted over a 3-month period with infertile women who had recently experienced a failed IVF cycle (T 0 ). Decisional conflict when they decided on terminating or continuing treatment (T 1 ) and decisional regret 3 months later (T 2 ) were measured. Participants reported their levels of depression, anxiety and FRQOL at three time points. A total of 151 participants completed all time points (attrition rate: 39%). The average age of participants was 37.2 years, and they had had 1.1 cycles (range: 0-8) on average at the time of study intake. The duration of the study was 2 years. Participants were infertile women who were not pregnant following an IVF cycle recruited from a university-affiliated assisted reproduction centre. Following the notification of a negative pregnancy result, patients were invited to complete measures of FRQOL, depression and anxiety across three time points and decisional conflict and decisional regret at T 1 and T 2 respectively. Decisional regret partially mediated the effect of decisional conflict on overall and treatment-specific FRQOL (P IVF cycle (P IVF cycle. Healthcare professionals should be aware of the psychological ramifications of

A Novel Method for Decoding Any High-Order Hidden Markov Model

Directory of Open Access Journals (Sweden)

Fei Ye

2014-01-01

Full Text Available This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model. This method provides a unified algorithm framework for decoding hidden Markov models including the first-order hidden Markov model and any high-order hidden Markov model.

Observation uncertainty in reversible Markov chains.

Science.gov (United States)

Metzner, Philipp; Weber, Marcus; Schütte, Christof

2010-09-01

In many applications one is interested in finding a simplified model which captures the essential dynamical behavior of a real life process. If the essential dynamics can be assumed to be (approximately) memoryless then a reasonable choice for a model is a Markov model whose parameters are estimated by means of Bayesian inference from an observed time series. We propose an efficient Monte Carlo Markov chain framework to assess the uncertainty of the Markov model and related observables. The derived Gibbs sampler allows for sampling distributions of transition matrices subject to reversibility and/or sparsity constraints. The performance of the suggested sampling scheme is demonstrated and discussed for a variety of model examples. The uncertainty analysis of functions of the Markov model under investigation is discussed in application to the identification of conformations of the trialanine molecule via Robust Perron Cluster Analysis (PCCA+) .

Finite Markov processes and their applications

CERN Document Server

Iosifescu, Marius

2007-01-01

A self-contained treatment of finite Markov chains and processes, this text covers both theory and applications. Author Marius Iosifescu, vice president of the Romanian Academy and director of its Center for Mathematical Statistics, begins with a review of relevant aspects of probability theory and linear algebra. Experienced readers may start with the second chapter, a treatment of fundamental concepts of homogeneous finite Markov chain theory that offers examples of applicable models.The text advances to studies of two basic types of homogeneous finite Markov chains: absorbing and ergodic ch

Markov chains models, algorithms and applications

CERN Document Server

Ching, Wai-Ki; Ng, Michael K; Siu, Tak-Kuen

2013-01-01

This new edition of Markov Chains: Models, Algorithms and Applications has been completely reformatted as a text, complete with end-of-chapter exercises, a new focus on management science, new applications of the models, and new examples with applications in financial risk management and modeling of financial data.This book consists of eight chapters.  Chapter 1 gives a brief introduction to the classical theory on both discrete and continuous time Markov chains. The relationship between Markov chains of finite states and matrix theory will also be highlighted. Some classical iterative methods

A scaling analysis of a cat and mouse Markov chain

NARCIS (Netherlands)

Litvak, Nelli; Robert, Philippe

2012-01-01

If ($C_n$) a Markov chain on a discrete state space $S$, a Markov chain ($C_n, M_n$) on the product space $S \\times S$, the cat and mouse Markov chain, is constructed. The first coordinate of this Markov chain behaves like the original Markov chain and the second component changes only when both

Perturbation theory for Markov chains via Wasserstein distance

NARCIS (Netherlands)

Rudolf, Daniel; Schweizer, Nikolaus

2017-01-01

Perturbation theory for Markov chains addresses the question of how small differences in the transition probabilities of Markov chains are reflected in differences between their distributions. We prove powerful and flexible bounds on the distance of the nth step distributions of two Markov chains

Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.

Science.gov (United States)

Chaubert-Pereira, Florence; Guédon, Yann; Lavergne, Christian; Trottier, Catherine

2010-09-01

Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates. © 2009, The International Biometric Society.

Approximate quantum Markov chains

CERN Document Server

Sutter, David

2018-01-01

This book is an introduction to quantum Markov chains and explains how this concept is connected to the question of how well a lost quantum mechanical system can be recovered from a correlated subsystem. To achieve this goal, we strengthen the data-processing inequality such that it reveals a statement about the reconstruction of lost information. The main difficulty in order to understand the behavior of quantum Markov chains arises from the fact that quantum mechanical operators do not commute in general. As a result we start by explaining two techniques of how to deal with non-commuting matrices: the spectral pinching method and complex interpolation theory. Once the reader is familiar with these techniques a novel inequality is presented that extends the celebrated Golden-Thompson inequality to arbitrarily many matrices. This inequality is the key ingredient in understanding approximate quantum Markov chains and it answers a question from matrix analysis that was open since 1973, i.e., if Lieb's triple ma...

Derivation of Markov processes that violate detailed balance

Science.gov (United States)

Lee, Julian

2018-03-01

Time-reversal symmetry of the microscopic laws dictates that the equilibrium distribution of a stochastic process must obey the condition of detailed balance. However, cyclic Markov processes that do not admit equilibrium distributions with detailed balance are often used to model systems driven out of equilibrium by external agents. I show that for a Markov model without detailed balance, an extended Markov model can be constructed, which explicitly includes the degrees of freedom for the driving agent and satisfies the detailed balance condition. The original cyclic Markov model for the driven system is then recovered as an approximation at early times by summing over the degrees of freedom for the driving agent. I also show that the widely accepted expression for the entropy production in a cyclic Markov model is actually a time derivative of an entropy component in the extended model. Further, I present an analytic expression for the entropy component that is hidden in the cyclic Markov model.

Quantum Markov Chain Mixing and Dissipative Engineering

DEFF Research Database (Denmark)

Kastoryano, Michael James

2012-01-01

This thesis is the fruit of investigations on the extension of ideas of Markov chain mixing to the quantum setting, and its application to problems of dissipative engineering. A Markov chain describes a statistical process where the probability of future events depends only on the state...... of the system at the present point in time, but not on the history of events. Very many important processes in nature are of this type, therefore a good understanding of their behaviour has turned out to be very fruitful for science. Markov chains always have a non-empty set of limiting distributions...... (stationary states). The aim of Markov chain mixing is to obtain (upper and/or lower) bounds on the number of steps it takes for the Markov chain to reach a stationary state. The natural quantum extensions of these notions are density matrices and quantum channels. We set out to develop a general mathematical...

Markov chains and semi-Markov models in time-to-event analysis.

Science.gov (United States)

Abner, Erin L; Charnigo, Richard J; Kryscio, Richard J

2013-10-25

A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields.

Phase Transitions for Quantum XY-Model on the Cayley Tree of Order Three in Quantum Markov Chain Scheme

International Nuclear Information System (INIS)

Mukhamedov, Farrukh; Saburov, Mansoor

2010-06-01

In the present paper we study forward Quantum Markov Chains (QMC) defined on a Cayley tree. Using the tree structure of graphs, we give a construction of quantum Markov chains on a Cayley tree. By means of such constructions we prove the existence of a phase transition for the XY-model on a Cayley tree of order three in QMC scheme. By the phase transition we mean the existence of two distinct QMC for the given family of interaction operators {K }. (author)

Fitting Hidden Markov Models to Psychological Data

Directory of Open Access Journals (Sweden)

Ingmar Visser

2002-01-01

Full Text Available Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive statistics for model selection and model assessment are lacking in the psychological literature. We present model selection and model assessment statistics that are particularly useful in applying hidden Markov models in psychology. These statistics are presented and evaluated by simulation studies for a toy example. We compare AIC, BIC and related criteria and introduce a prediction error measure for assessing goodness-of-fit. In a simulation study, two methods of fitting equality constraints are compared. In two illustrative examples with experimental data we apply selection criteria, fit models with constraints and assess goodness-of-fit. First, data from a concept identification task is analyzed. Hidden Markov models provide a flexible approach to analyzing such data when compared to other modeling methods. Second, a novel application of hidden Markov models in implicit learning is presented. Hidden Markov models are used in this context to quantify knowledge that subjects express in an implicit learning task. This method of analyzing implicit learning data provides a comprehensive approach for addressing important theoretical issues in the field.

Zipf exponent of trajectory distribution in the hidden Markov model

Science.gov (United States)

Bochkarev, V. V.; Lerner, E. Yu

2014-03-01

This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different.

Zipf exponent of trajectory distribution in the hidden Markov model

International Nuclear Information System (INIS)

Bochkarev, V V; Lerner, E Yu

2014-01-01

This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different

Irreversible Local Markov Chains with Rapid Convergence towards Equilibrium

Science.gov (United States)

Kapfer, Sebastian C.; Krauth, Werner

2017-12-01

We study the continuous one-dimensional hard-sphere model and present irreversible local Markov chains that mix on faster time scales than the reversible heat bath or Metropolis algorithms. The mixing time scales appear to fall into two distinct universality classes, both faster than for reversible local Markov chains. The event-chain algorithm, the infinitesimal limit of one of these Markov chains, belongs to the class presenting the fastest decay. For the lattice-gas limit of the hard-sphere model, reversible local Markov chains correspond to the symmetric simple exclusion process (SEP) with periodic boundary conditions. The two universality classes for irreversible Markov chains are realized by the totally asymmetric SEP (TASEP), and by a faster variant (lifted TASEP) that we propose here. We discuss how our irreversible hard-sphere Markov chains generalize to arbitrary repulsive pair interactions and carry over to higher dimensions through the concept of lifted Markov chains and the recently introduced factorized Metropolis acceptance rule.

Decision making regarding prophylactic mastectomy: stability of preferences and the impact of anticipated feelings of regret.

Science.gov (United States)

van Dijk, Sandra; van Roosmalen, Mariëlle S; Otten, Wilma; Stalmeier, Peep F M

2008-05-10

Women who test positive for a BRCA1/2 mutation face difficult choices to manage their breast cancer risk; one of these choices is whether to opt for prophylactic mastectomy. Few data are available about this decision-making process. The current study provides data regarding the stability of risk-management preferences over time and the factors that are associated with these preferences. We analyzed data from 338 women who opted for breast cancer antigen (BRCA) testing. First, we prospectively assessed preferences of 80 BRCA mutation carriers at five different points in time ranging from 1 week after blood sampling up to 9 months after BRCA-test disclosure. Second, we applied univariate and multivariate regression analyses to examine which medical, sociodemographic, and psychological factors are related to a preference for prophylactic mastectomy. Ninety percent of the women already indicated a preference regarding risk management at baseline. Moreover, most women had stable preferences over time. Furthermore, anticipated feelings of regret in case of a hypothetical breast cancer diagnosis in the near future were strongly related to risk-management preference (odds ratio = 8.93; P preferences. Many of them may be sensitive to the possibility of regret in case of a bad outcome. We discuss whether possible regret in the future is a rational reason for opting for prophylactic mastectomy, or whether it signifies an emotional coping process or strategy in which the future costs are no longer fully considered.

Selecting Products Considering the Regret Behavior of Consumer: A Decision Support Model Based on Online Ratings

Directory of Open Access Journals (Sweden)

Xia Liang

2018-05-01

Full Text Available With the remarkable promotion of e-commerce platforms, consumers increasingly prefer to purchase products online. Online ratings facilitate consumers to choose among products. Thus, to help consumers effectively select products, it is necessary to provide decision support methods for consumers to trade online. Considering the decision makers are bounded rational, this paper proposes a novel decision support model for product selection based on online ratings, in which the regret aversion behavior of consumers is formulated. Massive online ratings provided by experienced consumers for alternative products associated with several evaluation attributes are obtained by software finders. Then, the evaluations of alternative products in format of stochastic variables are conducted. To select a desirable alternative product, a novel method is introduced to calculate gain and loss degrees of each alternative over others. Considering the regret behavior of consumers in the product selection process, the regret and rejoice values of alternative products for consumer are computed to obtain the perceived utility values of alternative products. According to the prior order of the evaluation attributes provided by the consumer, the prior weights of attributes are determined based on the perceived utility values of alternative products. Furthermore, the overall perceived utility values of alternative products are obtained to generate a ranking result. Finally, a practical example from Zol.com.cn for tablet computer selection is used to demonstrate the feasibility and practically of the proposed model.

Reliability measures for indexed semi-Markov chains applied to wind energy production

International Nuclear Information System (INIS)

D'Amico, Guglielmo; Petroni, Filippo; Prattico, Flavio

2015-01-01

The computation of the dependability measures is a crucial point in many engineering problems as well as in the planning and development of a wind farm. In this paper we address the issue of energy production by wind turbines by using an indexed semi-Markov chain as a model of wind speed. We present the mathematical model, the data and technical characteristics of a commercial wind turbine (Aircon HAWT-10kW). We show how to compute some of the main dependability measures such as reliability, availability and maintainability functions. We compare the results of the model with real energy production obtained from data available in the Lastem station (Italy) and sampled every 10 min. - Highlights: • Semi-Markov models. • Time series generation of wind speed. • Computation of availability, reliability and maintainability.

Decoding and modelling of time series count data using Poisson hidden Markov model and Markov ordinal logistic regression models.

Science.gov (United States)

Sebastian, Tunny; Jeyaseelan, Visalakshi; Jeyaseelan, Lakshmanan; Anandan, Shalini; George, Sebastian; Bangdiwala, Shrikant I

2018-01-01

Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions and the parameters of the component Poisson distributions are governed by an m-state Markov chain with an unknown transition probability matrix are explained here. These methods were applied to the data on Vibrio cholerae counts reported every month for 11-year span at Christian Medical College, Vellore, India. Using Viterbi algorithm, the best estimate of the state sequence was obtained and hence the transition probability matrix. The mean passage time between the states were estimated. The 95% confidence interval for the mean passage time was estimated via Monte Carlo simulation. The three hidden states of the estimated Markov chain are labelled as 'Low', 'Moderate' and 'High' with the mean counts of 1.4, 6.6 and 20.2 and the estimated average duration of stay of 3, 3 and 4 months, respectively. Environmental risk factors were studied using Markov ordinal logistic regression analysis. No significant association was found between disease severity levels and climate components.

Probabilistic Reachability for Parametric Markov Models

DEFF Research Database (Denmark)

Hahn, Ernst Moritz; Hermanns, Holger; Zhang, Lijun

2011-01-01

Given a parametric Markov model, we consider the problem of computing the rational function expressing the probability of reaching a given set of states. To attack this principal problem, Daws has suggested to first convert the Markov chain into a finite automaton, from which a regular expression...

Lesson Development for English Learners in Content Area Settings: Key Considerations. Q&A with Sarah Catherine K. Moore, Ph.D. 2016 Educator Effectiveness Webinar Series

Science.gov (United States)

Moore, Sarah Catherine K.

2016-01-01

In this webinar, Dr. Sarah Catherine K. Moore, Program Director at the Center for Applied Linguistics, outlined factors for content area teachers to consider as they design and deliver lessons for mainstream classrooms that include English learner (EL) students. This Q&A addressed the questions participants had for Dr. Moore following the…

Prediction of inspection intervals using the Markov analysis; Prediccion de intervalos de inspeccion utilizando analisis de Markov

Energy Technology Data Exchange (ETDEWEB)

Rea, R.; Arellano, J. [IIE, Calle Reforma 113, Col. Palmira, Cuernavaca, Morelos (Mexico)]. e-mail: rrea@iie.org.mx

2005-07-01

To solve the unmanageable number of states of Markov of systems that have a great number of components, it is intends a modification to the method of Markov, denominated Markov truncated analysis, in which is assumed that it is worthless the dependence among faults of components. With it the number of states is increased in a lineal way (not exponential) with the number of components of the system, simplifying the analysis vastly. As example, the proposed method was applied to the system HPCS of the CLV considering its 18 main components. It thinks about that each component can take three states: operational, with hidden fault and with revealed fault. Additionally, it takes into account the configuration of the system HPCS by means of a block diagram of dependability to estimate their unavailability at level system. The results of the model here proposed are compared with other methods and approaches used to simplify the Markov analysis. It also intends the modification of the intervals of inspection of three components of the system HPCS. This finishes with base in the developed Markov model and in the maximum time allowed by the code ASME (NUREG-1482) to inspect components of systems that are in reservation in nuclear power plants. (Author)

Stencil method: a Markov model for transport in porous media

Science.gov (United States)

Delgoshaie, A. H.; Tchelepi, H.; Jenny, P.

2016-12-01

In porous media the transport of fluid is dominated by flow-field heterogeneity resulting from the underlying transmissibility field. Since the transmissibility is highly uncertain, many realizations of a geological model are used to describe the statistics of the transport phenomena in a Monte Carlo framework. One possible way to avoid the high computational cost of physics-based Monte Carlo simulations is to model the velocity field as a Markov process and use Markov Chain Monte Carlo. In previous works multiple Markov models for discrete velocity processes have been proposed. These models can be divided into two general classes of Markov models in time and Markov models in space. Both of these choices have been shown to be effective to some extent. However some studies have suggested that the Markov property cannot be confirmed for a temporal Markov process; Therefore there is not a consensus about the validity and value of Markov models in time. Moreover, previous spacial Markov models have only been used for modeling transport on structured networks and can not be readily applied to model transport in unstructured networks. In this work we propose a novel approach for constructing a Markov model in time (stencil method) for a discrete velocity process. The results form the stencil method are compared to previously proposed spacial Markov models for structured networks. The stencil method is also applied to unstructured networks and can successfully describe the dispersion of particles in this setting. Our conclusion is that both temporal Markov models and spacial Markov models for discrete velocity processes can be valid for a range of model parameters. Moreover, we show that the stencil model can be more efficient in many practical settings and is suited to model dispersion both on structured and unstructured networks.

Timed Comparisons of Semi-Markov Processes

DEFF Research Database (Denmark)

Pedersen, Mathias Ruggaard; Larsen, Kim Guldstrand; Bacci, Giorgio

2018-01-01

-Markov processes, and investigate the question of how to compare two semi-Markov processes with respect to their time-dependent behaviour. To this end, we introduce the relation of being “faster than” between processes and study its algorithmic complexity. Through a connection to probabilistic automata we obtain...

Markov-modulated and feedback fluid queues

NARCIS (Netherlands)

Scheinhardt, Willem R.W.

1998-01-01

In the last twenty years the field of Markov-modulated fluid queues has received considerable attention. In these models a fluid reservoir receives and/or releases fluid at rates which depend on the actual state of a background Markov chain. In the first chapter of this thesis we give a short

Monte Carlo Simulation of Markov, Semi-Markov, and Generalized Semi- Markov Processes in Probabilistic Risk Assessment

Science.gov (United States)

English, Thomas

2005-01-01

A standard tool of reliability analysis used at NASA-JSC is the event tree. An event tree is simply a probability tree, with the probabilities determining the next step through the tree specified at each node. The nodal probabilities are determined by a reliability study of the physical system at work for a particular node. The reliability study performed at a node is typically referred to as a fault tree analysis, with the potential of a fault tree existing.for each node on the event tree. When examining an event tree it is obvious why the event tree/fault tree approach has been adopted. Typical event trees are quite complex in nature, and the event tree/fault tree approach provides a systematic and organized approach to reliability analysis. The purpose of this study was two fold. Firstly, we wanted to explore the possibility that a semi-Markov process can create dependencies between sojourn times (the times it takes to transition from one state to the next) that can decrease the uncertainty when estimating time to failures. Using a generalized semi-Markov model, we studied a four element reliability model and were able to demonstrate such sojourn time dependencies. Secondly, we wanted to study the use of semi-Markov processes to introduce a time variable into the event tree diagrams that are commonly developed in PRA (Probabilistic Risk Assessment) analyses. Event tree end states which change with time are more representative of failure scenarios than are the usual static probability-derived end states.

Maximizing Entropy over Markov Processes

DEFF Research Database (Denmark)

Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis

2013-01-01

The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of an system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code....

Maximizing entropy over Markov processes

DEFF Research Database (Denmark)

Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis

2014-01-01

The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of a system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code. © 2014 Elsevier...

A scaling analysis of a cat and mouse Markov chain

NARCIS (Netherlands)

Litvak, Nelli; Robert, Philippe

Motivated by an original on-line page-ranking algorithm, starting from an arbitrary Markov chain $(C_n)$ on a discrete state space ${\\cal S}$, a Markov chain $(C_n,M_n)$ on the product space ${\\cal S}^2$, the cat and mouse Markov chain, is constructed. The first coordinate of this Markov chain

Probability distributions for Markov chain based quantum walks

Science.gov (United States)

Balu, Radhakrishnan; Liu, Chaobin; Venegas-Andraca, Salvador E.

2018-01-01

We analyze the probability distributions of the quantum walks induced from Markov chains by Szegedy (2004). The first part of this paper is devoted to the quantum walks induced from finite state Markov chains. It is shown that the probability distribution on the states of the underlying Markov chain is always convergent in the Cesaro sense. In particular, we deduce that the limiting distribution is uniform if the transition matrix is symmetric. In the case of a non-symmetric Markov chain, we exemplify that the limiting distribution of the quantum walk is not necessarily identical with the stationary distribution of the underlying irreducible Markov chain. The Szegedy scheme can be extended to infinite state Markov chains (random walks). In the second part, we formulate the quantum walk induced from a lazy random walk on the line. We then obtain the weak limit of the quantum walk. It is noted that the current quantum walk appears to spread faster than its counterpart-quantum walk on the line driven by the Grover coin discussed in literature. The paper closes with an outlook on possible future directions.

A test of multiple correlation temporal window characteristic of non-Markov processes

Science.gov (United States)

Arecchi, F. T.; Farini, A.; Megna, N.

2016-03-01

We introduce a sensitive test of memory effects in successive events. The test consists of a combination K of binary correlations at successive times. K decays monotonically from K = 1 for uncorrelated events as a Markov process. For a monotonic memory fading, K1 temporal window in cognitive tasks consisting of the visual identification of the front face of the Necker cube after a previous presentation of the same. We speculate that memory effects provide a temporal window with K>1 and this experiment could be a possible first step towards a better comprehension of this phenomenon. The K>1 behaviour is maximal at an inter-measurement time τ around 2s with inter-subject differences. The K>1 persists over a time window of 1s around τ; outside this window the K1 window in pairs of successive perceptions suggests that, at variance with single visual stimuli eliciting a suitable response, a pair of stimuli shortly separated in time displays mutual correlations.

Context Tree Estimation in Variable Length Hidden Markov Models

OpenAIRE

Dumont, Thierry

2011-01-01

We address the issue of context tree estimation in variable length hidden Markov models. We propose an estimator of the context tree of the hidden Markov process which needs no prior upper bound on the depth of the context tree. We prove that the estimator is strongly consistent. This uses information-theoretic mixture inequalities in the spirit of Finesso and Lorenzo(Consistent estimation of the order for Markov and hidden Markov chains(1990)) and E.Gassiat and S.Boucheron (Optimal error exp...

A Minimax Regret Analysis of Flood Risk Management Strategies Under Climate Change Uncertainty and Emerging Information

NARCIS (Netherlands)

Pol, van der T.D.; Gabbert, S.; Weikard, H.P.; Ierland, van E.C.; Hendrix, E.M.T.

2017-01-01

This paper studies the dynamic application of the minimax regret (MR) decision criterion to identify robust flood risk management strategies under climate change uncertainty and emerging information. An MR method is developed that uses multiple learning scenarios, for example about sea level rise

Modeling Uncertainty of Directed Movement via Markov Chains

Directory of Open Access Journals (Sweden)

YIN Zhangcai

2015-10-01

Full Text Available Probabilistic time geography (PTG is suggested as an extension of (classical time geography, in order to present the uncertainty of an agent located at the accessible position by probability. This may provide a quantitative basis for most likely finding an agent at a location. In recent years, PTG based on normal distribution or Brown bridge has been proposed, its variance, however, is irrelevant with the agent's speed or divergent with the increase of the speed; so they are difficult to take into account application pertinence and stability. In this paper, a new method is proposed to model PTG based on Markov chain. Firstly, a bidirectional conditions Markov chain is modeled, the limit of which, when the moving speed is large enough, can be regarded as the Brown bridge, thus has the characteristics of digital stability. Then, the directed movement is mapped to Markov chains. The essential part is to build step length, the state space and transfer matrix of Markov chain according to the space and time position of directional movement, movement speed information, to make sure the Markov chain related to the movement speed. Finally, calculating continuously the probability distribution of the directed movement at any time by the Markov chains, it can be get the possibility of an agent located at the accessible position. Experimental results show that, the variance based on Markov chains not only is related to speed, but also is tending towards stability with increasing the agent's maximum speed.

Markov chains analytic and Monte Carlo computations

CERN Document Server

Graham, Carl

2014-01-01

Markov Chains: Analytic and Monte Carlo Computations introduces the main notions related to Markov chains and provides explanations on how to characterize, simulate, and recognize them. Starting with basic notions, this book leads progressively to advanced and recent topics in the field, allowing the reader to master the main aspects of the classical theory. This book also features: Numerous exercises with solutions as well as extended case studies.A detailed and rigorous presentation of Markov chains with discrete time and state space.An appendix presenting probabilistic notions that are nec

Inhomogeneous Markov point processes by transformation

DEFF Research Database (Denmark)

Jensen, Eva B. Vedel; Nielsen, Linda Stougaard

2000-01-01

We construct parametrized models for point processes, allowing for both inhomogeneity and interaction. The inhomogeneity is obtained by applying parametrized transformations to homogeneous Markov point processes. An interesting model class, which can be constructed by this transformation approach......, is that of exponential inhomogeneous Markov point processes. Statistical inference For such processes is discussed in some detail....

Markov Networks in Evolutionary Computation

CERN Document Server

Shakya, Siddhartha

2012-01-01

Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs).  EDAs have arisen as one of the most successful experiences in the application of machine learning methods in optimization, mainly due to their efficiency to solve complex real-world optimization problems and their suitability for theoretical analysis. This book focuses on the different steps involved in the conception, implementation and application of EDAs that use Markov networks, and undirected models in general. It can serve as a general introduction to EDAs but covers also an important current void in the study of these algorithms by explaining the specificities and benefits of modeling optimization problems by means of undirected probabilistic models. All major developments to date in the progressive introduction of Markov networks based EDAs are reviewed in the book. Hot current researc...

Markov trace on the Yokonuma-Hecke algebra

International Nuclear Information System (INIS)

Juyumaya, J.

2002-11-01

The objective of this note is to prove that there exists a Markov trace on the Yokonuma-Hecke algebra. A motivation to define a Markov trace is to get polynomial invariants for knots in the sense of Jones construction. (author)

Introduction to the numerical solutions of Markov chains

CERN Document Server

Stewart, Williams J

1994-01-01

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse - and applications are increasingly being found in such areas as engineering, computer science, economics, and education. To apply the techniques to real problems, however, it is necessary to understand how Markov chains can be solved numerically. In this book, the first to offer a systematic and detailed treatment of the numerical solution of Markov chains, William Stewart provides scientists on many levels with the power to put this theory to use in the actual world, where it has applications in areas as diverse as engineering, economics, and education. His efforts make for essential reading in a rapidly growing field. Here, Stewart explores all aspects of numerically computing solutions of Markov chains, especially when the state is huge. He provides extensive background to both discrete-time and continuous-time Markov chains and examines many different numerical computing metho...

Adolescents' Pregnancy Intentions, Wantedness, and Regret: Cross-Lagged Relations with Mental Health and Harsh Parenting

Science.gov (United States)

East, Patricia L.; Chien, Nina C.; Barber, Jennifer S.

2012-01-01

The authors used cross-lagged analyses to examine the across-time influences on and consequences of adolescents' pregnancy intentions, wantedness, and regret. One hundred pregnant Latina adolescents were studied during pregnancy and at 6 and 12 months postpartum. The results revealed 4 main findings: (a) similar to what has been found in adult…

Investigating the effects of consumption-associated cues on disappointment, regret and post-consumption behaviours

OpenAIRE

Hossain, Muhammad Ismail

2017-01-01

Consumers invariably encounter both positive and negative consumption experiences in their lives. Prior research finds that negative consumption experiences result in particular affective and behavioural reactions. This research focuses on how consumers respond to consumption-associated cues, in particular, causal attributions, expectations, and perceived information search, in terms of feelings of disappointment and regret, and how these emotions subsequently influence consumers’ post consum...

The Independence of Markov's Principle in Type Theory

DEFF Research Database (Denmark)

Coquand, Thierry; Mannaa, Bassel

2017-01-01

for the generic point of this model. Instead we design an extension of type theory, which intuitively extends type theory by the addition of a generic point of Cantor space. We then show the consistency of this extension by a normalization argument. Markov's principle does not hold in this extension......In this paper, we show that Markov's principle is not derivable in dependent type theory with natural numbers and one universe. One way to prove this would be to remark that Markov's principle does not hold in a sheaf model of type theory over Cantor space, since Markov's principle does not hold......, and it follows that it cannot be proved in type theory....

Stochastic demand patterns for Markov service facilities with neutral and active periods

International Nuclear Information System (INIS)

Csenki, Attila

2009-01-01

In an earlier paper, a closed form expression was obtained for the joint interval reliability of a Markov system with a partitioned state space S=U union D, i.e. for the probability that the system will reside in the set of up states U throughout the union of some specific disjoint time intervals I l =[θ l ,θ l +ζ l ],l=1,...,k. The deterministic time intervals I l formed a demand pattern specifying the desired active periods. In the present paper, we admit stochastic demand patterns by assuming that the lengths of the active periods, ζ l , as well as the lengths of the neutral periods, θ l -(θ l-1 +ζ l-1 ), are random. We explore two mechanisms for modelling random demand: (1) by alternating renewal processes; (2) by sojourn times of some continuous time Markov chain with a partitioned state space. The first construction results in an expression in terms of a revised version of the moment generating functions of the sojourns of the alternating renewal process. The second construction involves the probability that a Markov chain follows certain patterns of visits to some groups of states and yields an expression using Kronecker matrix operations. The model of a small computer system is analysed to exemplify the ideas

Random regret-based discrete-choice modelling: an application to healthcare.

Science.gov (United States)

de Bekker-Grob, Esther W; Chorus, Caspar G

2013-07-01

A new modelling approach for analysing data from discrete-choice experiments (DCEs) has been recently developed in transport economics based on the notion of regret minimization-driven choice behaviour. This so-called Random Regret Minimization (RRM) approach forms an alternative to the dominant Random Utility Maximization (RUM) approach. The RRM approach is able to model semi-compensatory choice behaviour and compromise effects, while being as parsimonious and formally tractable as the RUM approach. Our objectives were to introduce the RRM modelling approach to healthcare-related decisions, and to investigate its usefulness in this domain. Using data from DCEs aimed at determining valuations of attributes of osteoporosis drug treatments and human papillomavirus (HPV) vaccinations, we empirically compared RRM models, RUM models and Hybrid RUM-RRM models in terms of goodness of fit, parameter ratios and predicted choice probabilities. In terms of model fit, the RRM model did not outperform the RUM model significantly in the case of the osteoporosis DCE data (p = 0.21), whereas in the case of the HPV DCE data, the Hybrid RUM-RRM model outperformed the RUM model (p implied by the two models can vary substantially. Differences in model fit between RUM, RRM and Hybrid RUM-RRM were found to be small. Although our study did not show significant differences in parameter ratios, the RRM and Hybrid RUM-RRM models did feature considerable differences in terms of the trade-offs implied by these ratios. In combination, our results suggest that RRM and Hybrid RUM-RRM modelling approach hold the potential of offering new and policy-relevant insights for health researchers and policy makers.

Generated dynamics of Markov and quantum processes

CERN Document Server

Janßen, Martin

2016-01-01

This book presents Markov and quantum processes as two sides of a coin called generated stochastic processes. It deals with quantum processes as reversible stochastic processes generated by one-step unitary operators, while Markov processes are irreversible stochastic processes generated by one-step stochastic operators. The characteristic feature of quantum processes are oscillations, interference, lots of stationary states in bounded systems and possible asymptotic stationary scattering states in open systems, while the characteristic feature of Markov processes are relaxations to a single stationary state. Quantum processes apply to systems where all variables, that control reversibility, are taken as relevant variables, while Markov processes emerge when some of those variables cannot be followed and are thus irrelevant for the dynamic description. Their absence renders the dynamic irreversible. A further aim is to demonstrate that almost any subdiscipline of theoretical physics can conceptually be put in...

Markov Models for Handwriting Recognition

CERN Document Server

Plotz, Thomas

2011-01-01

Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden

Cascaded K-means convolutional feature learner and its application to face recognition

Science.gov (United States)

Zhou, Daoxiang; Yang, Dan; Zhang, Xiaohong; Huang, Sheng; Feng, Shu

2017-09-01

Currently, considerable efforts have been devoted to devise image representation. However, handcrafted methods need strong domain knowledge and show low generalization ability, and conventional feature learning methods require enormous training data and rich parameters tuning experience. A lightened feature learner is presented to solve these problems with application to face recognition, which shares similar topology architecture as a convolutional neural network. Our model is divided into three components: cascaded convolution filters bank learning layer, nonlinear processing layer, and feature pooling layer. Specifically, in the filters learning layer, we use K-means to learn convolution filters. Features are extracted via convoluting images with the learned filters. Afterward, in the nonlinear processing layer, hyperbolic tangent is employed to capture the nonlinear feature. In the feature pooling layer, to remove the redundancy information and incorporate the spatial layout, we exploit multilevel spatial pyramid second-order pooling technique to pool the features in subregions and concatenate them together as the final representation. Extensive experiments on four representative datasets demonstrate the effectiveness and robustness of our model to various variations, yielding competitive recognition results on extended Yale B and FERET. In addition, our method achieves the best identification performance on AR and labeled faces in the wild datasets among the comparative methods.

Markov processes characterization and convergence

CERN Document Server

Ethier, Stewart N

2009-01-01

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists."[A]nyone who works with Markov processes whose state space is uncountably infinite will need this most impressive book as a guide and reference."-American Scientist"There is no question but that space should immediately be reserved for [this] book on the library shelf. Those who aspire to mastery of the contents should also reserve a large number of long winter evenings."-Zentralblatt f?r Mathematik und ihre Grenzgebiete/Mathematics Abstracts"Ethier and Kurtz have produced an excellent treatment of the modern theory of Markov processes that [is] useful both as a reference work and as a graduate textbook."-Journal of Statistical PhysicsMarkov Proce...

Renewal characterization of Markov modulated Poisson processes

Directory of Open Access Journals (Sweden)

Marcel F. Neuts

1989-01-01

Full Text Available A Markov Modulated Poisson Process (MMPP M(t defined on a Markov chain J(t is a pure jump process where jumps of M(t occur according to a Poisson process with intensity λi whenever the Markov chain J(t is in state i. M(t is called strongly renewal (SR if M(t is a renewal process for an arbitrary initial probability vector of J(t with full support on P={i:λi>0}. M(t is called weakly renewal (WR if there exists an initial probability vector of J(t such that the resulting MMPP is a renewal process. The purpose of this paper is to develop general characterization theorems for the class SR and some sufficiency theorems for the class WR in terms of the first passage times of the bivariate Markov chain [J(t,M(t]. Relevance to the lumpability of J(t is also studied.

Markov chain aggregation for agent-based models

CERN Document Server

Banisch, Sven

2016-01-01

This self-contained text develops a Markov chain approach that makes the rigorous analysis of a class of microscopic models that specify the dynamics of complex systems at the individual level possible. It presents a general framework of aggregation in agent-based and related computational models, one which makes use of lumpability and information theory in order to link the micro and macro levels of observation. The starting point is a microscopic Markov chain description of the dynamical process in complete correspondence with the dynamical behavior of the agent-based model (ABM), which is obtained by considering the set of all possible agent configurations as the state space of a huge Markov chain. An explicit formal representation of a resulting “micro-chain” including microscopic transition rates is derived for a class of models by using the random mapping representation of a Markov process. The type of probability distribution used to implement the stochastic part of the model, which defines the upd...

NonMarkov Ito Processes with 1- state memory

Science.gov (United States)

McCauley, Joseph L.

2010-08-01

A Markov process, by definition, cannot depend on any previous state other than the last observed state. An Ito process implies the Fokker-Planck and Kolmogorov backward time partial differential eqns. for transition densities, which in turn imply the Chapman-Kolmogorov eqn., but without requiring the Markov condition. We present a class of Ito process superficially resembling Markov processes, but with 1-state memory. In finance, such processes would obey the efficient market hypothesis up through the level of pair correlations. These stochastic processes have been mislabeled in recent literature as 'nonlinear Markov processes'. Inspired by Doob and Feller, who pointed out that the ChapmanKolmogorov eqn. is not restricted to Markov processes, we exhibit a Gaussian Ito transition density with 1-state memory in the drift coefficient that satisfies both of Kolmogorov's partial differential eqns. and also the Chapman-Kolmogorov eqn. In addition, we show that three of the examples from McKean's seminal 1966 paper are also nonMarkov Ito processes. Last, we show that the transition density of the generalized Black-Scholes type partial differential eqn. describes a martingale, and satisfies the ChapmanKolmogorov eqn. This leads to the shortest-known proof that the Green function of the Black-Scholes eqn. with variable diffusion coefficient provides the so-called martingale measure of option pricing.

A New GMRES(m Method for Markov Chains

Directory of Open Access Journals (Sweden)

Bing-Yuan Pu

2013-01-01

Full Text Available This paper presents a class of new accelerated restarted GMRES method for calculating the stationary probability vector of an irreducible Markov chain. We focus on the mechanism of this new hybrid method by showing how to periodically combine the GMRES and vector extrapolation method into a much efficient one for improving the convergence rate in Markov chain problems. Numerical experiments are carried out to demonstrate the efficiency of our new algorithm on several typical Markov chain problems.

Markov chains and mixing times

CERN Document Server

Levin, David A; Wilmer, Elizabeth L

2009-01-01

This book is an introduction to the modern approach to the theory of Markov chains. The main goal of this approach is to determine the rate of convergence of a Markov chain to the stationary distribution as a function of the size and geometry of the state space. The authors develop the key tools for estimating convergence times, including coupling, strong stationary times, and spectral methods. Whenever possible, probabilistic methods are emphasized. The book includes many examples and provides brief introductions to some central models of statistical mechanics. Also provided are accounts of r

Why Do Tertiary Education Graduates Regret Their Study Program? A Comparison between Spain and the Netherlands

Science.gov (United States)

Kucel, Aleksander; Vilalta-Bufi, Montserrat

2013-01-01

In this paper we investigate the determinants of regret of study program for tertiary education graduates in Spain and the Netherlands. These two countries differ in their educational system in terms of the tracking structure in their secondary education and the strength of their education-labor market linkages in tertiary education. Therefore, by…

Anatomy of regret: a developmental view of the depressive position and a critical turn toward love and creativity in the transforming schizoid personality.

Science.gov (United States)

Kavaler-Adler, Susan

2004-03-01

This article deals with critical psychic transformation in a schizoid personality disorder that evolves in an object relations psychoanalysis in which "developmental mourning" plays a central role. Within a mourning process that allows for the grieving of loss related to arrested separation-individuation development, the analysand confronts the existential grief of regret that had always unconsciously haunted her. The unconscious guilt related to the existential grief of regret had caused much dissociation of self-experience and affect states. The analysand acknowledges her own part in the destruction of primal and current relationships after the traumatic impact of her early life is understood. This allows her to repair current relationships, both within her internal and external worlds so that she can open to capacities for love and creativity. The analysand's courage to consciously grapple with her regret (loss and guilt combined) allows her to relinquish self-sabotaging character defenses such as contempt and emotional withdrawl. Consequently, a second marriage is salvaged and enriched, and the analysand's relationship with her two children is dramatically improved.

Markov Chain Modelling for Short-Term NDVI Time Series Forecasting

Directory of Open Access Journals (Sweden)

Stepčenko Artūrs

2016-12-01

Full Text Available In this paper, the NDVI time series forecasting model has been developed based on the use of discrete time, continuous state Markov chain of suitable order. The normalised difference vegetation index (NDVI is an indicator that describes the amount of chlorophyll (the green mass and shows the relative density and health of vegetation; therefore, it is an important variable for vegetation forecasting. A Markov chain is a stochastic process that consists of a state space. This stochastic process undergoes transitions from one state to another in the state space with some probabilities. A Markov chain forecast model is flexible in accommodating various forecast assumptions and structures. The present paper discusses the considerations and techniques in building a Markov chain forecast model at each step. Continuous state Markov chain model is analytically described. Finally, the application of the proposed Markov chain model is illustrated with reference to a set of NDVI time series data.

Switching Markov chains for a holistic modeling of SIS unavailability

International Nuclear Information System (INIS)

Mechri, Walid; Simon, Christophe; BenOthman, Kamel

2015-01-01

This paper proposes a holistic approach to model the Safety Instrumented Systems (SIS). The model is based on Switching Markov Chain and integrates several parameters like Common Cause Failure, Imperfect Proof testing, partial proof testing, etc. The basic concepts of Switching Markov Chain applied to reliability analysis are introduced and a model to compute the unavailability for a case study is presented. The proposed Switching Markov Chain allows us to assess the effect of each parameter on the SIS performance. The proposed method ensures the relevance of the results. - Highlights: • A holistic approach to model the unavailability safety systems using Switching Markov chains. • The model integrates several parameters like probability of failure due to the test, the probability of not detecting a failure in a test. • The basic concepts of the Switching Markov Chains are introduced and applied to compute the unavailability for safety systems. • The proposed Switching Markov Chain allows assessing the effect of each parameter on the chemical reactor performance

Markov and mixed models with applications

DEFF Research Database (Denmark)

Mortensen, Stig Bousgaard

This thesis deals with mathematical and statistical models with focus on applications in pharmacokinetic and pharmacodynamic (PK/PD) modelling. These models are today an important aspect of the drug development in the pharmaceutical industry and continued research in statistical methodology within...... or uncontrollable factors in an individual. Modelling using SDEs also provides new tools for estimation of unknown inputs to a system and is illustrated with an application to estimation of insulin secretion rates in diabetic patients. Models for the eect of a drug is a broader area since drugs may affect...... for non-parametric estimation of Markov processes are proposed to give a detailed description of the sleep process during the night. Statistically the Markov models considered for sleep states are closely related to the PK models based on SDEs as both models share the Markov property. When the models...

Joint Markov Blankets in Feature Sets Extracted from Wavelet Packet Decompositions

Directory of Open Access Journals (Sweden)

Gert Van Dijck

2011-07-01

Full Text Available Since two decades, wavelet packet decompositions have been shown effective as a generic approach to feature extraction from time series and images for the prediction of a target variable. Redundancies exist between the wavelet coefficients and between the energy features that are derived from the wavelet coefficients. We assess these redundancies in wavelet packet decompositions by means of the Markov blanket filtering theory. We introduce the concept of joint Markov blankets. It is shown that joint Markov blankets are a natural extension of Markov blankets, which are defined for single features, to a set of features. We show that these joint Markov blankets exist in feature sets consisting of the wavelet coefficients. Furthermore, we prove that wavelet energy features from the highest frequency resolution level form a joint Markov blanket for all other wavelet energy features. The joint Markov blanket theory indicates that one can expect an increase of classification accuracy with the increase of the frequency resolution level of the energy features.

Bayesian analysis of Markov point processes

DEFF Research Database (Denmark)

Berthelsen, Kasper Klitgaard; Møller, Jesper

2006-01-01

Recently Møller, Pettitt, Berthelsen and Reeves introduced a new MCMC methodology for drawing samples from a posterior distribution when the likelihood function is only specified up to a normalising constant. We illustrate the method in the setting of Bayesian inference for Markov point processes...... a partially ordered Markov point process as the auxiliary variable. As the method requires simulation from the "unknown" likelihood, perfect simulation algorithms for spatial point processes become useful....

Quantum Enhanced Inference in Markov Logic Networks.

Science.gov (United States)

Wittek, Peter; Gogolin, Christian

2017-04-19

Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning.

Quantum Enhanced Inference in Markov Logic Networks

Science.gov (United States)

Wittek, Peter; Gogolin, Christian

2017-04-01

Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning.

Mentorship in Grades 5 through 12 Gifted Vocal Music Programs: Learners' and Educators' Perceptions of Mentorship

Science.gov (United States)

Brown, Jimmy Lee

2017-01-01

Although the implementation of effective instructional practice is paramount to the academic success of gifted music programs in kindergarten through twelfth grade (K-12), many learners in gifted music programs lack critical thinking skills, self-directed learning, a learner-centered paradigm, and learner-mentor relationship during instruction.…

Sampling rare fluctuations of discrete-time Markov chains

Science.gov (United States)

Whitelam, Stephen

2018-03-01

We describe a simple method that can be used to sample the rare fluctuations of discrete-time Markov chains. We focus on the case of Markov chains with well-defined steady-state measures, and derive expressions for the large-deviation rate functions (and upper bounds on such functions) for dynamical quantities extensive in the length of the Markov chain. We illustrate the method using a series of simple examples, and use it to study the fluctuations of a lattice-based model of active matter that can undergo motility-induced phase separation.

Markov's theorem and algorithmically non-recognizable combinatorial manifolds

International Nuclear Information System (INIS)

Shtan'ko, M A

2004-01-01

We prove the theorem of Markov on the existence of an algorithmically non-recognizable combinatorial n-dimensional manifold for every n≥4. We construct for the first time a concrete manifold which is algorithmically non-recognizable. A strengthened form of Markov's theorem is proved using the combinatorial methods of regular neighbourhoods and handle theory. The proofs coincide for all n≥4. We use Borisov's group with insoluble word problem. It has two generators and twelve relations. The use of this group forms the base for proving the strengthened form of Markov's theorem

Extending Markov Automata with State and Action Rewards

NARCIS (Netherlands)

Guck, Dennis; Timmer, Mark; Blom, Stefan; Bertrand, N.; Bortolussi, L.

This presentation introduces the Markov Reward Automaton (MRA), an extension of the Markov automaton that allows the modelling of systems incorporating rewards in addition to nondeterminism, discrete probabilistic choice and continuous stochastic timing. Our models support both rewards that are

Automatic creation of Markov models for reliability assessment of safety instrumented systems

International Nuclear Information System (INIS)

Guo Haitao; Yang Xianhui

2008-01-01

After the release of new international functional safety standards like IEC 61508, people care more for the safety and availability of safety instrumented systems. Markov analysis is a powerful and flexible technique to assess the reliability measurements of safety instrumented systems, but it is fallible and time-consuming to create Markov models manually. This paper presents a new technique to automatically create Markov models for reliability assessment of safety instrumented systems. Many safety related factors, such as failure modes, self-diagnostic, restorations, common cause and voting, are included in Markov models. A framework is generated first based on voting, failure modes and self-diagnostic. Then, repairs and common-cause failures are incorporated into the framework to build a complete Markov model. Eventual simplification of Markov models can be done by state merging. Examples given in this paper show how explosively the size of Markov model increases as the system becomes a little more complicated as well as the advancement of automatic creation of Markov models

The moderating role of self-efficacy beliefs in the relationship between anticipated feelings of regret and condom use

NARCIS (Netherlands)

Bakker, AB; Buunk, BP; Manstead, ASR

1997-01-01

This prospective study examined how the feelings of regret and self-blame one anticipates after engaging in unsafe sex affect condom use in new sexual relationships. The central theoretical question is whether self-efficacy perceptions can moderate the relationship between anticipated feelings and

Coding with partially hidden Markov models

DEFF Research Database (Denmark)

Forchhammer, Søren; Rissanen, J.

1995-01-01

Partially hidden Markov models (PHMM) are introduced. They are a variation of the hidden Markov models (HMM) combining the power of explicit conditioning on past observations and the power of using hidden states. (P)HMM may be combined with arithmetic coding for lossless data compression. A general...... 2-part coding scheme for given model order but unknown parameters based on PHMM is presented. A forward-backward reestimation of parameters with a redefined backward variable is given for these models and used for estimating the unknown parameters. Proof of convergence of this reestimation is given....... The PHMM structure and the conditions of the convergence proof allows for application of the PHMM to image coding. Relations between the PHMM and hidden Markov models (HMM) are treated. Results of coding bi-level images with the PHMM coding scheme is given. The results indicate that the PHMM can adapt...

Asymptotics for Estimating Equations in Hidden Markov Models

DEFF Research Database (Denmark)

Hansen, Jørgen Vinsløv; Jensen, Jens Ledet

Results on asymptotic normality for the maximum likelihood estimate in hidden Markov models are extended in two directions. The stationarity assumption is relaxed, which allows for a covariate process influencing the hidden Markov process. Furthermore a class of estimating equations is considered...

Joint interval reliability for Markov systems with an application in transmission line reliability

International Nuclear Information System (INIS)

Csenki, Attila

2007-01-01

We consider Markov reliability models whose finite state space is partitioned into the set of up states U and the set of down states D . Given a collection of k disjoint time intervals I l =[t l ,t l +x l ], l=1,...,k, the joint interval reliability is defined as the probability of the system being in U for all time instances in I 1 union ... union I k . A closed form expression is derived here for the joint interval reliability for this class of models. The result is applied to power transmission lines in a two-state fluctuating environment. We use the Linux versions of the free packages Maxima and Scilab in our implementation for symbolic and numerical work, respectively

Learning and dynamic choices under uncertainty: from weighted regret and rejoice to expected utility

OpenAIRE

Zagonari, Fabio

2016-01-01

This paper identifies the globally stable conditions under which an individual facing the same choice in many subsequent times learns to behave as prescribed by the expected-utility model. To do so, the analysis moves from the relevant behavioural models suggested by psychology (i.e., weighted probabilities applied to regret and rejoice theory), and by updating probability estimations and outcome preferences according to the learning models suggested by neuroscience (i.e., adaptive learning a...

Prediction of inspection intervals using the Markov analysis

International Nuclear Information System (INIS)

Rea, R.; Arellano, J.

2005-01-01

To solve the unmanageable number of states of Markov of systems that have a great number of components, it is intends a modification to the method of Markov, denominated Markov truncated analysis, in which is assumed that it is worthless the dependence among faults of components. With it the number of states is increased in a lineal way (not exponential) with the number of components of the system, simplifying the analysis vastly. As example, the proposed method was applied to the system HPCS of the CLV considering its 18 main components. It thinks about that each component can take three states: operational, with hidden fault and with revealed fault. Additionally, it takes into account the configuration of the system HPCS by means of a block diagram of dependability to estimate their unavailability at level system. The results of the model here proposed are compared with other methods and approaches used to simplify the Markov analysis. It also intends the modification of the intervals of inspection of three components of the system HPCS. This finishes with base in the developed Markov model and in the maximum time allowed by the code ASME (NUREG-1482) to inspect components of systems that are in reservation in nuclear power plants. (Author)

Benchmarking of a Markov multizone model of contaminant transport.

Science.gov (United States)

Jones, Rachael M; Nicas, Mark

2014-10-01

A Markov chain model previously applied to the simulation of advection and diffusion process of gaseous contaminants is extended to three-dimensional transport of particulates in indoor environments. The model framework and assumptions are described. The performance of the Markov model is benchmarked against simple conventional models of contaminant transport. The Markov model is able to replicate elutriation predictions of particle deposition with distance from a point source, and the stirred settling of respirable particles. Comparisons with turbulent eddy diffusion models indicate that the Markov model exhibits numerical diffusion in the first seconds after release, but over time accurately predicts mean lateral dispersion. The Markov model exhibits some instability with grid length aspect when turbulence is incorporated by way of the turbulent diffusion coefficient, and advection is present. However, the magnitude of prediction error may be tolerable for some applications and can be avoided by incorporating turbulence by way of fluctuating velocity (e.g. turbulence intensity). © The Author 2014. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Model Checking Markov Reward Models with Impulse Rewards

NARCIS (Netherlands)

Cloth, Lucia; Katoen, Joost-Pieter; Khattri, Maneesh; Pulungan, Reza; Bondavalli, Andrea; Haverkort, Boudewijn; Tang, Dong

This paper considers model checking of Markov reward models (MRMs), continuous-time Markov chains with state rewards as well as impulse rewards. The reward extension of the logic CSL (Continuous Stochastic Logic) is interpreted over such MRMs, and two numerical algorithms are provided to check the

Consistent Estimation of Partition Markov Models

Directory of Open Access Journals (Sweden)

Jesús E. García

2017-04-01

Full Text Available The Partition Markov Model characterizes the process by a partition L of the state space, where the elements in each part of L share the same transition probability to an arbitrary element in the alphabet. This model aims to answer the following questions: what is the minimal number of parameters needed to specify a Markov chain and how to estimate these parameters. In order to answer these questions, we build a consistent strategy for model selection which consist of: giving a size n realization of the process, finding a model within the Partition Markov class, with a minimal number of parts to represent the process law. From the strategy, we derive a measure that establishes a metric in the state space. In addition, we show that if the law of the process is Markovian, then, eventually, when n goes to infinity, L will be retrieved. We show an application to model internet navigation patterns.

The Learning Preferences of Digital Learners in K-12 Schools in China

Science.gov (United States)

Yang, Junfeng; Huang, Ronghuai; Kinshuk

2016-01-01

Students grown up with digital technology and Internet are called digital natives or net generation. All others, who grew up without so much immersion with digital technologies are called digital immigrants. Researchers held different ideas on whether a new generation of learners existed. One of the foci of the debate is on the appropriateness of…

Estimates and Standard Errors for Ratios of Normalizing Constants from Multiple Markov Chains via Regeneration.

Science.gov (United States)

Doss, Hani; Tan, Aixin

2014-09-01

In the classical biased sampling problem, we have k densities π 1 (·), …, π k (·), each known up to a normalizing constant, i.e. for l = 1, …, k , π l (·) = ν l (·)/ m l , where ν l (·) is a known function and m l is an unknown constant. For each l , we have an iid sample from π l , · and the problem is to estimate the ratios m l /m s for all l and all s . This problem arises frequently in several situations in both frequentist and Bayesian inference. An estimate of the ratios was developed and studied by Vardi and his co-workers over two decades ago, and there has been much subsequent work on this problem from many different perspectives. In spite of this, there are no rigorous results in the literature on how to estimate the standard error of the estimate. We present a class of estimates of the ratios of normalizing constants that are appropriate for the case where the samples from the π l 's are not necessarily iid sequences, but are Markov chains. We also develop an approach based on regenerative simulation for obtaining standard errors for the estimates of ratios of normalizing constants. These standard error estimates are valid for both the iid case and the Markov chain case.

Hidden Markov models applied to a subsequence of the Xylella fastidiosa genome

Directory of Open Access Journals (Sweden)

Silva Cibele Q. da

2003-01-01

Full Text Available Dependencies in DNA sequences are frequently modeled using Markov models. However, Markov chains cannot account for heterogeneity that may be present in different regions of the same DNA sequence. Hidden Markov models are more realistic than Markov models since they allow for the identification of heterogeneous regions of a DNA sequence. In this study we present an application of hidden Markov models to a subsequence of the Xylella fastidiosa DNA data. We found that a three-state model provides a good description for the data considered.

Markov decision processes in artificial intelligence

CERN Document Server

Sigaud, Olivier

2013-01-01

Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as Reinforcement Learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in Artificial Intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, Reinforcement Learning, Partially Observable MDPs, Markov games and the use of non-classical criteria). Then it presents more advanced research trends in the domain and gives some concrete examples using illustr

Prediction of Annual Rainfall Pattern Using Hidden Markov Model ...

African Journals Online (AJOL)

ADOWIE PERE

Hidden Markov model is very influential in stochastic world because of its ... the earth from the clouds. The usual ... Rainfall modelling and ... Markov Models have become popular tools ... environment sciences, University of Jos, plateau state,.

Markov Chain Monte Carlo Methods

Indian Academy of Sciences (India)

Keywords. Markov chain; state space; stationary transition probability; stationary distribution; irreducibility; aperiodicity; stationarity; M-H algorithm; proposal distribution; acceptance probability; image processing; Gibbs sampler.

Deteksi Fraud Menggunakan Metode Model Markov Tersembunyi Pada Proses Bisnis

Directory of Open Access Journals (Sweden)

Andrean Hutama Koosasi

2017-03-01

Full Text Available Model Markov Tersembunyi merupakan sebuah metode statistik berdasarkan Model Markov sederhana yang memodelkan sistem serta membaginya dalam 2 (dua state, state tersembunyi dan state observasi. Dalam pengerjaan tugas akhir ini, penulis mengusulkan penggunaan metode Model Markov Tersembunyi untuk menemukan fraud didalam sebuah pelaksanaan proses bisnis. Dengan penggunaan metode Model Markov Tersembunyi ini, maka pengamatan terhadap elemen penyusun sebuah kasus/kejadian, yakni beberapa aktivitas, akan diperoleh sebuah nilai peluang, yang sekaligus memberikan prediksi terhadap kasus/kejadian tersebut, sebuah fraud atau tidak. Hasil ekpserimen ini menunjukkan bahwa metode yang diusulkan mampu memberikan prediksi akhir dengan evaluasi TPR sebesar 87,5% dan TNR sebesar 99,4%.

Learner Satisfaction in Online Learning: An Analysis of the Perceived Impact of Learner-Social Media and Learner-Instructor Interaction

Science.gov (United States)

Andersen, Jeffery C.

2013-01-01

The purpose of this study was to determine the relationships between general course satisfaction, learner-instructor interaction, and the learner-social media interaction scores of participants. This study used an online survey with 60 questions to gather the participants' demographic data, learner-instructor interaction data, learner-social…

A Bayesian model for binary Markov chains

Directory of Open Access Journals (Sweden)

Belkheir Essebbar

2004-02-01

Full Text Available This note is concerned with Bayesian estimation of the transition probabilities of a binary Markov chain observed from heterogeneous individuals. The model is founded on the Jeffreys' prior which allows for transition probabilities to be correlated. The Bayesian estimator is approximated by means of Monte Carlo Markov chain (MCMC techniques. The performance of the Bayesian estimates is illustrated by analyzing a small simulated data set.

Transition Effect Matrices and Quantum Markov Chains

Science.gov (United States)

Gudder, Stan

2009-06-01

A transition effect matrix (TEM) is a quantum generalization of a classical stochastic matrix. By employing a TEM we obtain a quantum generalization of a classical Markov chain. We first discuss state and operator dynamics for a quantum Markov chain. We then consider various types of TEMs and vector states. In particular, we study invariant, equilibrium and singular vector states and investigate projective, bistochastic, invertible and unitary TEMs.

Joint interval reliability for Markov systems with an application in transmission line reliability

Energy Technology Data Exchange (ETDEWEB)

Csenki, Attila [School of Computing and Mathematics, University of Bradford, Bradford, West Yorkshire, BD7 1DP (United Kingdom)]. E-mail: a.csenki@bradford.ac.uk

2007-06-15

We consider Markov reliability models whose finite state space is partitioned into the set of up states {sub U} and the set of down states {sub D}. Given a collection of k disjoint time intervals I{sub l}=[t{sub l},t{sub l}+x{sub l}], l=1,...,k, the joint interval reliability is defined as the probability of the system being in {sub U} for all time instances in I{sub 1} union ... union I{sub k}. A closed form expression is derived here for the joint interval reliability for this class of models. The result is applied to power transmission lines in a two-state fluctuating environment. We use the Linux versions of the free packages Maxima and Scilab in our implementation for symbolic and numerical work, respectively.

Pathwise duals of monotone and additive Markov processes

Czech Academy of Sciences Publication Activity Database

Sturm, A.; Swart, Jan M.

-, - (2018) ISSN 0894-9840 R&D Projects: GA ČR GAP201/12/2613 Institutional support: RVO:67985556 Keywords : pathwise duality * monotone Markov process * additive Markov process * interacting particle system Subject RIV: BA - General Mathematics Impact factor: 0.854, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/swart-0465436.pdf

Markov bridges, bisection and variance reduction

DEFF Research Database (Denmark)

Asmussen, Søren; Hobolth, Asger

. In this paper we firstly consider the problem of generating sample paths from a continuous-time Markov chain conditioned on the endpoints using a new algorithm based on the idea of bisection. Secondly we study the potential of the bisection algorithm for variance reduction. In particular, examples are presented......Time-continuous Markov jump processes is a popular modelling tool in disciplines ranging from computational finance and operations research to human genetics and genomics. The data is often sampled at discrete points in time, and it can be useful to simulate sample paths between the datapoints...

Markov Chain Ontology Analysis (MCOA).

Science.gov (United States)

Frost, H Robert; McCray, Alexa T

2012-02-03

Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data. In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods. A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches.

STATISTICAL ANALYSIS OF NOTATIONAL AFL DATA USING CONTINUOUS TIME MARKOV CHAINS

Directory of Open Access Journals (Sweden)

Denny Meyer

2006-12-01

Full Text Available Animal biologists commonly use continuous time Markov chain models to describe patterns of animal behaviour. In this paper we consider the use of these models for describing AFL football. In particular we test the assumptions for continuous time Markov chain models (CTMCs, with time, distance and speed values associated with each transition. Using a simple event categorisation it is found that a semi-Markov chain model is appropriate for this data. This validates the use of Markov Chains for future studies in which the outcomes of AFL matches are simulated

Perturbed Markov chains

OpenAIRE

Solan, Eilon; Vieille, Nicolas

2015-01-01

We study irreducible time-homogenous Markov chains with finite state space in discrete time. We obtain results on the sensitivity of the stationary distribution and other statistical quantities with respect to perturbations of the transition matrix. We define a new closeness relation between transition matrices, and use graph-theoretic techniques, in contrast with the matrix analysis techniques previously used.

Recursive smoothers for hidden discrete-time Markov chains

Directory of Open Access Journals (Sweden)

Lakhdar Aggoun

2005-01-01

Full Text Available We consider a discrete-time Markov chain observed through another Markov chain. The proposed model extends models discussed by Elliott et al. (1995. We propose improved recursive formulae to update smoothed estimates of processes related to the model. These recursive estimates are used to update the parameter of the model via the expectation maximization (EM algorithm.

An introduction to hidden Markov models for biological sequences

DEFF Research Database (Denmark)

Krogh, Anders Stærmose

1998-01-01

A non-matematical tutorial on hidden Markov models (HMMs) plus a description of one of the applications of HMMs: gene finding.......A non-matematical tutorial on hidden Markov models (HMMs) plus a description of one of the applications of HMMs: gene finding....

Portfolio allocation under the vendor managed inventory: A Markov ...

African Journals Online (AJOL)

Portfolio allocation under the vendor managed inventory: A Markov decision process. ... Journal of Applied Sciences and Environmental Management ... This study provides a review of Markov decision processes and investigates its suitability for solutions to portfolio allocation problems under vendor managed inventory in ...

Classification of customer lifetime value models using Markov chain

Science.gov (United States)

Permana, Dony; Pasaribu, Udjianna S.; Indratno, Sapto W.; Suprayogi

2017-10-01

A firm’s potential reward in future time from a customer can be determined by customer lifetime value (CLV). There are some mathematic methods to calculate it. One method is using Markov chain stochastic model. Here, a customer is assumed through some states. Transition inter the states follow Markovian properties. If we are given some states for a customer and the relationships inter states, then we can make some Markov models to describe the properties of the customer. As Markov models, CLV is defined as a vector contains CLV for a customer in the first state. In this paper we make a classification of Markov Models to calculate CLV. Start from two states of customer model, we make develop in many states models. The development a model is based on weaknesses in previous model. Some last models can be expected to describe how real characters of customers in a firm.

Technology-Based Literacy Instruction for English Language Learners

Science.gov (United States)

White, Erin L.; Gillard, Sharlett

2011-01-01

There is a growing need to implement an alternative and viable solution in U.S. K-12 schools that will address the ever-growing gap that the rapidly growing English language learner (ELL) population presents. This article examines various technology-based solutions, and their potential impact. The systematic implementation of these…

What Do Teachers Need to Support English Learners?

Science.gov (United States)

Gomez, Marjorie N.; Diarrassouba, Nagnon

2014-01-01

This study explored K-8 teachers' perceptions of their preparation and the challenges they encountered in delivering instruction to culturally and linguistically diverse learners. Using a mixed method research design, data were collected through a web-based survey from teachers in the state of Michigan. Researchers used chi-square tests to…

A Markov Process Inspired Cellular Automata Model of Road Traffic

OpenAIRE

Wang, Fa; Li, Li; Hu, Jianming; Ji, Yan; Yao, Danya; Zhang, Yi; Jin, Xuexiang; Su, Yuelong; Wei, Zheng

2008-01-01

To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process whose stationary distribution corresponds to the observed distribution of practical gaps. The multiformity of this Markov process provides the model enough flexibility to describe various driving behaviors. Two examples are given to show how to specialize i...

Why Do Learners Choose Online Learning: The Learners' Voices

Science.gov (United States)

Ilgaz, Hale; Gulbahar, Yasemin

2017-01-01

Offering many advantages to adult learners, e-Learning is now being recognized--and preferred--by more and more people, resulting in an increased number of distance learners in recent years. Numerous research studies focus on learner preferences for online learning, with most converging around the individual characteristics and differences, if not…

Partially Hidden Markov Models

DEFF Research Database (Denmark)

Forchhammer, Søren Otto; Rissanen, Jorma

1996-01-01

Partially Hidden Markov Models (PHMM) are introduced. They differ from the ordinary HMM's in that both the transition probabilities of the hidden states and the output probabilities are conditioned on past observations. As an illustration they are applied to black and white image compression where...

Estimation with Right-Censored Observations Under A Semi-Markov Model.

Science.gov (United States)

Zhao, Lihui; Hu, X Joan

2013-06-01

The semi-Markov process often provides a better framework than the classical Markov process for the analysis of events with multiple states. The purpose of this paper is twofold. First, we show that in the presence of right censoring, when the right end-point of the support of the censoring time is strictly less than the right end-point of the support of the semi-Markov kernel, the transition probability of the semi-Markov process is nonidentifiable, and the estimators proposed in the literature are inconsistent in general. We derive the set of all attainable values for the transition probability based on the censored data, and we propose a nonparametric inference procedure for the transition probability using this set. Second, the conventional approach to constructing confidence bands is not applicable for the semi-Markov kernel and the sojourn time distribution. We propose new perturbation resampling methods to construct these confidence bands. Different weights and transformations are explored in the construction. We use simulation to examine our proposals and illustrate them with hospitalization data from a recent cancer survivor study.

Representing Lumped Markov Chains by Minimal Polynomials over Field GF(q)

Science.gov (United States)

Zakharov, V. M.; Shalagin, S. V.; Eminov, B. F.

2018-05-01

A method has been proposed to represent lumped Markov chains by minimal polynomials over a finite field. The accuracy of representing lumped stochastic matrices, the law of lumped Markov chains depends linearly on the minimum degree of polynomials over field GF(q). The method allows constructing the realizations of lumped Markov chains on linear shift registers with a pre-defined “linear complexity”.

Efficient Incorporation of Markov Random Fields in Change Detection

DEFF Research Database (Denmark)

Aanæs, Henrik; Nielsen, Allan Aasbjerg; Carstensen, Jens Michael

2009-01-01

of noise, implying that the pixel-wise classifier is also noisy. There is thus a need for incorporating local homogeneity constraints into such a change detection framework. For this modelling task Markov Random Fields are suitable. Markov Random Fields have, however, previously been plagued by lack...

First hitting probabilities for semi markov chains and estimation

DEFF Research Database (Denmark)

Georgiadis, Stylianos

2017-01-01

We first consider a stochastic system described by an absorbing semi-Markov chain with finite state space and we introduce the absorption probability to a class of recurrent states. Afterwards, we study the first hitting probability to a subset of states for an irreducible semi-Markov chain...

Whose voice matters? Learners

Directory of Open Access Journals (Sweden)

Sarah Bansilal

2010-01-01

Full Text Available International and national mathematics studies have revealed the poor mathematics skills of South African learners. An essential tool that can be used to improve learners' mathematical skills is for educators to use effective feedback. Our purpose in this study was to elicit learners' understanding and expectations of teacher assessment feedback. The study was conducted with five Grade 9 mathematics learners. Data were generated from one group interview, seven journal entries by each learner, video-taped classroom observations and researcher field notes. The study revealed that the learners have insightful perceptions of the concept of educator feedback. While some learners viewed educator feedback as a tool to probe their understanding, others viewed it as a mechanism to get the educator's point of view. A significant finding of the study was that learners viewed educator assessment feedback as instrumental in building or breaking their self-confidence.

Inhomogeneous Markov Models for Describing Driving Patterns

DEFF Research Database (Denmark)

Iversen, Emil Banning; Møller, Jan K.; Morales, Juan Miguel

2017-01-01

. Specifically, an inhomogeneous Markov model that captures the diurnal variation in the use of a vehicle is presented. The model is defined by the time-varying probabilities of starting and ending a trip, and is justified due to the uncertainty associated with the use of the vehicle. The model is fitted to data...... collected from the actual utilization of a vehicle. Inhomogeneous Markov models imply a large number of parameters. The number of parameters in the proposed model is reduced using B-splines....

Inhomogeneous Markov Models for Describing Driving Patterns

DEFF Research Database (Denmark)

Iversen, Jan Emil Banning; Møller, Jan Kloppenborg; Morales González, Juan Miguel

. Specically, an inhomogeneous Markov model that captures the diurnal variation in the use of a vehicle is presented. The model is dened by the time-varying probabilities of starting and ending a trip and is justied due to the uncertainty associated with the use of the vehicle. The model is tted to data...... collected from the actual utilization of a vehicle. Inhomogeneous Markov models imply a large number of parameters. The number of parameters in the proposed model is reduced using B-splines....

Subharmonic projections for a quantum Markov semigroup

International Nuclear Information System (INIS)

Fagnola, Franco; Rebolledo, Rolando

2002-01-01

This article introduces a concept of subharmonic projections for a quantum Markov semigroup, in view of characterizing the support projection of a stationary state in terms of the semigroup generator. These results, together with those of our previous article [J. Math. Phys. 42, 1296 (2001)], lead to a method for proving the existence of faithful stationary states. This is often crucial in the analysis of ergodic properties of quantum Markov semigroups. The method is illustrated by applications to physical models

Formative evaluation of an adaptive game for engaging learners of programming concepts in K-12

Directory of Open Access Journals (Sweden)

Renny S. N. Lindberg

2018-06-01

Full Text Available As the global demand for programmers is soaring, several countries have integrated programming into their K-12 curricula. Finding effective ways to engage children in programming education is an important objective. One effective method for this can be presenting learning materials via games, which are known to increase engagement and motivation. Current programming education games often focus on a single genre and offer one-size-fits-all experience to heterogeneous learners. In this study, we presented Minerva, a multi-genre (adventure, action, puzzle game to engage elementary school students in learning programming concepts. The game content is adapted to play and learning styles of the player to personalize the gameplay. We conducted a formative mixed-method evaluation of Minerva with 32 Korean 6th grade students who played the game and compared their learning outcomes with 32 6th grade students who studied the same concepts using handouts. The results indicated that, in terms of retention, learning was equally effective in both groups. Furthermore, the game was shown to facilitate engagement among the students. These results, together with uncovered issues, will guide Minerva’s further development.

Logics and Models for Stochastic Analysis Beyond Markov Chains

DEFF Research Database (Denmark)

Zeng, Kebin

, because of the generality of ME distributions, we have to leave the world of Markov chains. To support ME distributions with multiple exits, we introduce a multi-exits ME distribution together with a process algebra MEME to express the systems having the semantics as Markov renewal processes with ME...

Analyzing the profit-loss sharing contracts with Markov model

Directory of Open Access Journals (Sweden)

Imam Wahyudi

2016-12-01

Full Text Available The purpose of this paper is to examine how to use first order Markov chain to build a reliable monitoring system for the profit-loss sharing based contracts (PLS as the mode of financing contracts in Islamic bank with censored continuous-time observations. The paper adopts the longitudinal analysis with the first order Markov chain framework. Laplace transform was used with homogenous continuous time assumption, from discretized generator matrix, to generate the transition matrix. Various metrics, i.e.: eigenvalue and eigenvector were used to test the first order Markov chain assumption. Cox semi parametric model was used also to analyze the momentum and waiting time effect as non-Markov behavior. The result shows that first order Markov chain is powerful as a monitoring tool for Islamic banks. We find that waiting time negatively affected present rating downgrade (upgrade significantly. Likewise, momentum covariate showed negative effect. Finally, the result confirms that different origin rating have different movement behavior. The paper explores the potential of Markov chain framework as a risk management tool for Islamic banks. It provides valuable insight and integrative model for banks to manage their borrower accounts. This model can be developed to be a powerful early warning system to identify which borrower needs to be monitored intensively. Ultimately, this model could potentially increase the efficiency, productivity and competitiveness of Islamic banks in Indonesia. The analysis used only rating data. Further study should be able to give additional information about the determinant factors of rating movement of the borrowers by incorporating various factors such as contract-related factors, bank-related factors, borrower-related factors and macroeconomic factors.

On mean reward variance in semi-Markov processes

Czech Academy of Sciences Publication Activity Database

Sladký, Karel

2005-01-01

Roč. 62, č. 3 (2005), s. 387-397 ISSN 1432-2994 R&D Projects: GA ČR(CZ) GA402/05/0115; GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : Markov and semi-Markov processes with rewards * variance of cumulative reward * asymptotic behaviour Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.259, year: 2005

Learner corpus profiles the case of Romanian learner English

CERN Document Server

Chitez, Madalina

2014-01-01

The first three chapters of the book offer relevant information on the new methodological approach, learner corpus profiling, and the exemplifying case, Romanian Learner English. The description of the Romanian Corpus of Learner English is also given special attention. The following three chapters include corpus-based frequency analyses of selected grammatical categories (articles, prepositions, genitives), combined with error analyses. In the concluding discussion, the book summarizes the features compiled as lexico-grammatical profiles.

Personal recommender systems for learners in lifelong learning: requirements, techniques and model

NARCIS (Netherlands)

Drachsler, Hendrik; Hummel, Hans; Koper, Rob

2007-01-01

Drachsler, H., Hummel, H. G. K., & Koper, R. (2008). Personal recommender systems for learners in lifelong learning: requirements, techniques and model. International Journal of Learning Technology, 3(4), 404-423.

Learner Personas in CALL

Science.gov (United States)

Heift, Trude

2007-01-01

In examining the titles of this year's conference presentations, the author noticed quite a few papers that focus on learner-specific issues, for instance, papers that address learning styles, learner needs, personality and learning, learner modeling and, more generally, pedagogical issues that deal with individual learner differences in…

Time series segmentation: a new approach based on Genetic Algorithm and Hidden Markov Model

Science.gov (United States)

Toreti, A.; Kuglitsch, F. G.; Xoplaki, E.; Luterbacher, J.

2009-04-01

The subdivision of a time series into homogeneous segments has been performed using various methods applied to different disciplines. In climatology, for example, it is accompanied by the well-known homogenization problem and the detection of artificial change points. In this context, we present a new method (GAMM) based on Hidden Markov Model (HMM) and Genetic Algorithm (GA), applicable to series of independent observations (and easily adaptable to autoregressive processes). A left-to-right hidden Markov model, estimating the parameters and the best-state sequence, respectively, with the Baum-Welch and Viterbi algorithms, was applied. In order to avoid the well-known dependence of the Baum-Welch algorithm on the initial condition, a Genetic Algorithm was developed. This algorithm is characterized by mutation, elitism and a crossover procedure implemented with some restrictive rules. Moreover the function to be minimized was derived following the approach of Kehagias (2004), i.e. it is the so-called complete log-likelihood. The number of states was determined applying a two-fold cross-validation procedure (Celeux and Durand, 2008). Being aware that the last issue is complex, and it influences all the analysis, a Multi Response Permutation Procedure (MRPP; Mielke et al., 1981) was inserted. It tests the model with K+1 states (where K is the state number of the best model) if its likelihood is close to K-state model. Finally, an evaluation of the GAMM performances, applied as a break detection method in the field of climate time series homogenization, is shown. 1. G. Celeux and J.B. Durand, Comput Stat 2008. 2. A. Kehagias, Stoch Envir Res 2004. 3. P.W. Mielke, K.J. Berry, G.W. Brier, Monthly Wea Rev 1981.

Predicting Protein Secondary Structure with Markov Models

DEFF Research Database (Denmark)

Fischer, Paul; Larsen, Simon; Thomsen, Claus

2004-01-01

we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

Automated generation of partial Markov chain from high level descriptions

International Nuclear Information System (INIS)

Brameret, P.-A.; Rauzy, A.; Roussel, J.-M.

2015-01-01

We propose an algorithm to generate partial Markov chains from high level implicit descriptions, namely AltaRica models. This algorithm relies on two components. First, a variation on Dijkstra's algorithm to compute shortest paths in a graph. Second, the definition of a notion of distance to select which states must be kept and which can be safely discarded. The proposed method solves two problems at once. First, it avoids a manual construction of Markov chains, which is both tedious and error prone. Second, up the price of acceptable approximations, it makes it possible to push back dramatically the exponential blow-up of the size of the resulting chains. We report experimental results that show the efficiency of the proposed approach. - Highlights: • We generate Markov chains from a higher level safety modeling language (AltaRica). • We use a variation on Dijkstra's algorithm to generate partial Markov chains. • Hence we solve two problems: the first problem is the tedious manual construction of Markov chains. • The second problem is the blow-up of the size of the chains, at the cost of decent approximations. • The experimental results highlight the efficiency of the method

Status of teaching elementary science for English learners in science, mathematics and technology centered magnet schools

Science.gov (United States)

Han, Alyson Kim

According to the California Commission on Teacher Credentialing (2001), one in three students speaks a language other than English. Additionally, the Commission stated that a student is considered to be an English learner if the second language acquisition is English. In California more than 1.4 million English learners enter school speaking a variety of languages, and this number continues to rise. There is an imminent need to promote instructional strategies that support this group of diverse learners. Although this was not a California study, the results derived from the nationwide participants' responses provided a congruent assessment of the basic need to provide effective science teaching strategies to all English learners. The purpose of this study was to examine the status of elementary science teaching practices used with English learners in kindergarten through fifth grade in public mathematics, science, and technology-centered elementary magnet schools throughout the country. This descriptive research was designed to provide current information and to identify trends in the areas of curriculum and instruction for English learners in science themed magnet schools. This report described the status of elementary (grades K-5) school science instruction for English learners based on the responses of 116 elementary school teachers: 59 grade K-2, and 57 grade 3-5 teachers. Current research-based approaches support incorporating self-directed learning strategy, expository teaching strategy, active listening strategies, questioning strategies, wait time strategy, small group strategy, peer tutoring strategy, large group learning strategy, demonstrations strategy, formal debates strategy, review sessions strategy, mediated conversation strategy, cooperative learning strategy, and theme-based instruction into the curriculum to assist English learners in science education. Science Technology Society (STS) strategy, problem-based learning strategy, discovery learning

Noise can speed convergence in Markov chains.

Science.gov (United States)

Franzke, Brandon; Kosko, Bart

2011-10-01

A new theorem shows that noise can speed convergence to equilibrium in discrete finite-state Markov chains. The noise applies to the state density and helps the Markov chain explore improbable regions of the state space. The theorem ensures that a stochastic-resonance noise benefit exists for states that obey a vector-norm inequality. Such noise leads to faster convergence because the noise reduces the norm components. A corollary shows that a noise benefit still occurs if the system states obey an alternate norm inequality. This leads to a noise-benefit algorithm that requires knowledge of the steady state. An alternative blind algorithm uses only past state information to achieve a weaker noise benefit. Simulations illustrate the predicted noise benefits in three well-known Markov models. The first model is a two-parameter Ehrenfest diffusion model that shows how noise benefits can occur in the class of birth-death processes. The second model is a Wright-Fisher model of genotype drift in population genetics. The third model is a chemical reaction network of zeolite crystallization. A fourth simulation shows a convergence rate increase of 64% for states that satisfy the theorem and an increase of 53% for states that satisfy the corollary. A final simulation shows that even suboptimal noise can speed convergence if the noise applies over successive time cycles. Noise benefits tend to be sharpest in Markov models that do not converge quickly and that do not have strong absorbing states.

Composable Markov Building Blocks

NARCIS (Netherlands)

Evers, S.; Fokkinga, M.M.; Apers, Peter M.G.; Prade, H.; Subrahmanian, V.S.

2007-01-01

In situations where disjunct parts of the same process are described by their own first-order Markov models and only one model applies at a time (activity in one model coincides with non-activity in the other models), these models can be joined together into one. Under certain conditions, nearly all

Tornadoes and related damage costs: statistical modelling with a semi-Markov approach

Directory of Open Access Journals (Sweden)

Guglielmo D’Amico

2016-09-01

Full Text Available We propose a statistical approach to modelling for predicting and simulating occurrences of tornadoes and accumulated cost distributions over a time interval. This is achieved by modelling the tornado intensity, measured with the Fujita scale, as a stochastic process. Since the Fujita scale divides tornado intensity into six states, it is possible to model the tornado intensity by using Markov and semi-Markov models. We demonstrate that the semi-Markov approach is able to reproduce the duration effect that is detected in tornado occurrence. The superiority of the semi-Markov model as compared to the Markov chain model is also affirmed by means of a statistical test of hypothesis. As an application, we compute the expected value and the variance of the costs generated by the tornadoes over a given time interval in a given area. The paper contributes to the literature by demonstrating that semi-Markov models represent an effective tool for physical analysis of tornadoes as well as for the estimation of the economic damages to human things.

Self-Reevaluation and Anticipated Regret Did Not Change Attitude, Nor Perceived Distance in an Online Context

OpenAIRE

Crutzen, Rik; Cyr, Dianne; Taylor, Sarah E.; Lim, Eric; Ruiter, Robert A. C.

2017-01-01

Internet-delivered interventions can be effective in changing behavior, but more research is needed on effective elements of behavior change interventions. Moreover, although anonymity is one of the advantages of using an online context, it might also increase the perceived distance between the participant and the intervention. Hence, the current study investigated whether the behavior change methods of self-reevaluation and anticipated regret can be used to narrow the perceived distance and,...

Discounted semi-Markov decision processes : linear programming and policy iteration

NARCIS (Netherlands)

Wessels, J.; van Nunen, J.A.E.E.

1975-01-01

For semi-Markov decision processes with discounted rewards we derive the well known results regarding the structure of optimal strategies (nonrandomized, stationary Markov strategies) and the standard algorithms (linear programming, policy iteration). Our analysis is completely based on a primal

Discounted semi-Markov decision processes : linear programming and policy iteration

NARCIS (Netherlands)

Wessels, J.; van Nunen, J.A.E.E.

1974-01-01

For semi-Markov decision processes with discounted rewards we derive the well known results regarding the structure of optimal strategies (nonrandomized, stationary Markov strategies) and the standard algorithms (linear programming, policy iteration). Our analysis is completely based on a primal

Compositionality for Markov reward chains with fast and silent transitions

NARCIS (Netherlands)

Markovski, J.; Sokolova, A.; Trcka, N.; Vink, de E.P.

2009-01-01

A parallel composition is defined for Markov reward chains with stochastic discontinuity, and with fast and silent transitions. In this setting, compositionality with respect to the relevant aggregation preorders is established. For Markov reward chains with fast transitions the preorders are

Perturbation approach to scaled type Markov renewal processes with infinite mean

OpenAIRE

Pajor-Gyulai, Zsolt; Szász, Domokos

2010-01-01

Scaled type Markov renewal processes generalize classical renewal processes: renewal times come from a one parameter family of probability laws and the sequence of the parameters is the trajectory of an ergodic Markov chain. Our primary interest here is the asymptotic distribution of the Markovian parameter at time t \\to \\infty. The limit, of course, depends on the stationary distribution of the Markov chain. The results, however, are essentially different depending on whether the expectation...

Focus on Form, Learner Uptake and Subsequent Lexical Gains in Learners' Oral Production

Science.gov (United States)

Alcon-Soler, Eva

2009-01-01

This descriptive study reports findings on the relationship between focus on form, learner uptake and subsequent lexical gains in learners' oral production. The data for the study consisted in 17 45-minute audio-recorded teacher-led conversations, 204 learners' diaries (17 sessions x 12 learners) reporting what they had learned after each…

Detecting Structural Breaks using Hidden Markov Models

DEFF Research Database (Denmark)

Ntantamis, Christos

Testing for structural breaks and identifying their location is essential for econometric modeling. In this paper, a Hidden Markov Model (HMM) approach is used in order to perform these tasks. Breaks are defined as the data points where the underlying Markov Chain switches from one state to another....... The estimation of the HMM is conducted using a variant of the Iterative Conditional Expectation-Generalized Mixture (ICE-GEMI) algorithm proposed by Delignon et al. (1997), that permits analysis of the conditional distributions of economic data and allows for different functional forms across regimes...

Markov processes an introduction for physical scientists

CERN Document Server

Gillespie, Daniel T

1991-01-01

Markov process theory is basically an extension of ordinary calculus to accommodate functions whos time evolutions are not entirely deterministic. It is a subject that is becoming increasingly important for many fields of science. This book develops the single-variable theory of both continuous and jump Markov processes in a way that should appeal especially to physicists and chemists at the senior and graduate level.Key Features* A self-contained, prgamatic exposition of the needed elements of random variable theory* Logically integrated derviations of the Chapman-Kolmogorov e

Facilitating Professional Development for Teachers of English Language Learners

Science.gov (United States)

Molle, Daniella

2013-01-01

The study explores the process of facilitation in professional development for educators. The study relies on discourse analysis of interaction among K-12 teachers and administrators in a Midwestern U.S. state during a semester-long professional development program especially designed for educators working with English language learners (ELLs).…

Working with language learner histories from three perspectives: Teachers, learners and researchers

Directory of Open Access Journals (Sweden)

Sarah Mercer

2013-10-01

Full Text Available Recent developments in SLA, such as learner-centredness, social constructivism, the postmethod era, and complexity perspectives, have highlighted the need for more localized, situated understandings of teaching and learning and greater recognition of learner individuality and diversity. In this article, I suggest an effective way of meeting these needs is to employ learner histories. This powerful form of writing allows learners to use their L2 to engage in authentic, personally meaningful communication with others about their identities, experiences, perceptions and emotions related to their language learning histories. As a text type, they are able to facilitate a more holistic perspective of the learner’s life and reveal the unique interconnections that an individual makes across various domains. They also enable the situated, contextualised and dynamic nature of their learning experiences to become apparent and provide learners with a genuine, motivating purpose for writing. Exploring data generated in Austria with tertiary-level EFL learners, I seek to illustrate some of the rich potential of these text types from three perspectives, namely, those of the teacher, learner and researcher.

Composable Markov Building Blocks

NARCIS (Netherlands)

Evers, S.; Fokkinga, M.M.; Apers, Peter M.G.

2007-01-01

In situations where disjunct parts of the same process are described by their own first-order Markov models, these models can be joined together under the constraint that there can only be one activity at a time, i.e. the activities of one model coincide with non-activity in the other models. Under

Markov Chain Monte Carlo

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 7; Issue 3. Markov Chain Monte Carlo - Examples. Arnab Chakraborty. General Article Volume 7 Issue 3 March 2002 pp 25-34. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/007/03/0025-0034. Keywords.

Ethnolinguistically Relevant Pedagogy: Empowering English Language Learners in Physical Education

Science.gov (United States)

Burden, Joe W., Jr.; Columna, Luis; Hodge, Samuel R.; Mansilla, Patricia Martinez de la Vega

2013-01-01

People from diverse cultures interpret languages and gestures differently (Columna & Lieberman, 2011). It is not surprising, therefore, that communication differences may have negative implications for teachers and English language learners in K-12 physical education environments. To address this issue, we advocate preparing physical education…

Markov Chain Monte Carlo Methods

Indian Academy of Sciences (India)

Systat Software Asia-Pacific. Ltd., in Bangalore, where the technical work for the development of the statistical software Systat takes ... In Part 4, we discuss some applications of the Markov ... one can construct the joint probability distribution of.

The generalization ability of online SVM classification based on Markov sampling.

Science.gov (United States)

Xu, Jie; Yan Tang, Yuan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang

2015-03-01

In this paper, we consider online support vector machine (SVM) classification learning algorithms with uniformly ergodic Markov chain (u.e.M.c.) samples. We establish the bound on the misclassification error of an online SVM classification algorithm with u.e.M.c. samples based on reproducing kernel Hilbert spaces and obtain a satisfactory convergence rate. We also introduce a novel online SVM classification algorithm based on Markov sampling, and present the numerical studies on the learning ability of online SVM classification based on Markov sampling for benchmark repository. The numerical studies show that the learning performance of the online SVM classification algorithm based on Markov sampling is better than that of classical online SVM classification based on random sampling as the size of training samples is larger.

Prediction and generation of binary Markov processes: Can a finite-state fox catch a Markov mouse?

Science.gov (United States)

Ruebeck, Joshua B.; James, Ryan G.; Mahoney, John R.; Crutchfield, James P.

2018-01-01

Understanding the generative mechanism of a natural system is a vital component of the scientific method. Here, we investigate one of the fundamental steps toward this goal by presenting the minimal generator of an arbitrary binary Markov process. This is a class of processes whose predictive model is well known. Surprisingly, the generative model requires three distinct topologies for different regions of parameter space. We show that a previously proposed generator for a particular set of binary Markov processes is, in fact, not minimal. Our results shed the first quantitative light on the relative (minimal) costs of prediction and generation. We find, for instance, that the difference between prediction and generation is maximized when the process is approximately independently, identically distributed.

Prognostics for Steam Generator Tube Rupture using Markov Chain model

International Nuclear Information System (INIS)

Kim, Gibeom; Heo, Gyunyoung; Kim, Hyeonmin

2016-01-01

This paper will describe the prognostics method for evaluating and forecasting the ageing effect and demonstrate the procedure of prognostics for the Steam Generator Tube Rupture (SGTR) accident. Authors will propose the data-driven method so called MCMC (Markov Chain Monte Carlo) which is preferred to the physical-model method in terms of flexibility and availability. Degradation data is represented as growth of burst probability over time. Markov chain model is performed based on transition probability of state. And the state must be discrete variable. Therefore, burst probability that is continuous variable have to be changed into discrete variable to apply Markov chain model to the degradation data. The Markov chain model which is one of prognostics methods was described and the pilot demonstration for a SGTR accident was performed as a case study. The Markov chain model is strong since it is possible to be performed without physical models as long as enough data are available. However, in the case of the discrete Markov chain used in this study, there must be loss of information while the given data is discretized and assigned to the finite number of states. In this process, original information might not be reflected on prediction sufficiently. This should be noted as the limitation of discrete models. Now we will be studying on other prognostics methods such as GPM (General Path Model) which is also data-driven method as well as the particle filer which belongs to physical-model method and conducting comparison analysis

Rate estimation in partially observed Markov jump processes with measurement errors

OpenAIRE

Amrein, Michael; Kuensch, Hans R.

2010-01-01

We present a simulation methodology for Bayesian estimation of rate parameters in Markov jump processes arising for example in stochastic kinetic models. To handle the problem of missing components and measurement errors in observed data, we embed the Markov jump process into the framework of a general state space model. We do not use diffusion approximations. Markov chain Monte Carlo and particle filter type algorithms are introduced, which allow sampling from the posterior distribution of t...

Quantum Markov processes and applications in many-body systems

International Nuclear Information System (INIS)

Temme, P. K.

2010-01-01

This thesis is concerned with the investigation of quantum as well as classical Markov processes and their application in the field of strongly correlated many-body systems. A Markov process is a special kind of stochastic process, which is determined by an evolution that is independent of its history and only depends on the current state of the system. The application of Markov processes has a long history in the field of statistical mechanics and classical many-body theory. Not only are Markov processes used to describe the dynamics of stochastic systems, but they predominantly also serve as a practical method that allows for the computation of fundamental properties of complex many-body systems by means of probabilistic algorithms. The aim of this thesis is to investigate the properties of quantum Markov processes, i.e. Markov processes taking place in a quantum mechanical state space, and to gain a better insight into complex many-body systems by means thereof. Moreover, we formulate a novel quantum algorithm which allows for the computation of the thermal and ground states of quantum many-body systems. After a brief introduction to quantum Markov processes we turn to an investigation of their convergence properties. We find bounds on the convergence rate of the quantum process by generalizing geometric bounds found for classical processes. We generalize a distance measure that serves as the basis for our investigations, the chi-square divergence, to non-commuting probability spaces. This divergence allows for a convenient generalization of the detailed balance condition to quantum processes. We then devise the quantum algorithm that can be seen as the natural generalization of the ubiquitous Metropolis algorithm to simulate quantum many-body Hamiltonians. By this we intend to provide further evidence, that a quantum computer can serve as a fully-fledged quantum simulator, which is not only capable of describing the dynamical evolution of quantum systems, but

Exact asymptotics of probabilities of large deviations for Markov chains: the Laplace method

Energy Technology Data Exchange (ETDEWEB)

Fatalov, Vadim R [M. V. Lomonosov Moscow State University, Faculty of Mechanics and Mathematics, Moscow (Russian Federation)

2011-08-31

We prove results on exact asymptotics as n{yields}{infinity} for the expectations E{sub a} exp{l_brace}-{theta}{Sigma}{sub k=0}{sup n-1}g(X{sub k}){r_brace} and probabilities P{sub a}{l_brace}(1/n {Sigma}{sub k=0}{sup n-1}g(X{sub k})k}{r_brace}{sub k=1}{sup {infinity}} is a sequence of independent identically Laplace-distributed random variables, X{sub n}=X{sub 0}+{Sigma}{sub k=1}{sup n}{xi}{sub k}, n{>=}1, is the corresponding random walk on R, g(x) is a positive continuous function satisfying certain conditions, and d>0, {theta}>0, a element of R are fixed numbers. Our results are obtained using a new method which is developed in this paper: the Laplace method for the occupation time of discrete-time Markov chains. For g(x) one can take |x|{sup p}, log (|x|{sup p}+1), p>0, |x| log (|x|+1), or e{sup {alpha}|x|}-1, 0<{alpha}<1/2, x element of R, for example. We give a detailed treatment of the case when g(x)=|x| using Bessel functions to make explicit calculations.

Markov decision processes: a tool for sequential decision making under uncertainty.

Science.gov (United States)

Alagoz, Oguzhan; Hsu, Heather; Schaefer, Andrew J; Roberts, Mark S

2010-01-01

We provide a tutorial on the construction and evaluation of Markov decision processes (MDPs), which are powerful analytical tools used for sequential decision making under uncertainty that have been widely used in many industrial and manufacturing applications but are underutilized in medical decision making (MDM). We demonstrate the use of an MDP to solve a sequential clinical treatment problem under uncertainty. Markov decision processes generalize standard Markov models in that a decision process is embedded in the model and multiple decisions are made over time. Furthermore, they have significant advantages over standard decision analysis. We compare MDPs to standard Markov-based simulation models by solving the problem of the optimal timing of living-donor liver transplantation using both methods. Both models result in the same optimal transplantation policy and the same total life expectancies for the same patient and living donor. The computation time for solving the MDP model is significantly smaller than that for solving the Markov model. We briefly describe the growing literature of MDPs applied to medical decisions.

Temperature scaling method for Markov chains.

Science.gov (United States)

Crosby, Lonnie D; Windus, Theresa L

2009-01-22

The use of ab initio potentials in Monte Carlo simulations aimed at investigating the nucleation kinetics of water clusters is complicated by the computational expense of the potential energy determinations. Furthermore, the common desire to investigate the temperature dependence of kinetic properties leads to an urgent need to reduce the expense of performing simulations at many different temperatures. A method is detailed that allows a Markov chain (obtained via Monte Carlo) at one temperature to be scaled to other temperatures of interest without the need to perform additional large simulations. This Markov chain temperature-scaling (TeS) can be generally applied to simulations geared for numerous applications. This paper shows the quality of results which can be obtained by TeS and the possible quantities which may be extracted from scaled Markov chains. Results are obtained for a 1-D analytical potential for which the exact solutions are known. Also, this method is applied to water clusters consisting of between 2 and 5 monomers, using Dynamical Nucleation Theory to determine the evaporation rate constant for monomer loss. Although ab initio potentials are not utilized in this paper, the benefit of this method is made apparent by using the Dang-Chang polarizable classical potential for water to obtain statistical properties at various temperatures.

Preservice Teachers' Developing Conceptions of Teaching English Learners

Science.gov (United States)

Kelly, Laura Beth

2018-01-01

In this study, 12 preservice teachers in a community college English as a second language (ESL) K-12 teacher education program drew pictures and wrote descriptions of teachers teaching English language learners (ELLs) at the beginning and end of an ESL methods course. Using content analysis, the researcher analyzed the drawings and descriptions…

Fermionic Markov Chains

OpenAIRE

Fannes, Mark; Wouters, Jeroen

2012-01-01

We study a quantum process that can be considered as a quantum analogue for the classical Markov process. We specifically construct a version of these processes for free Fermions. For such free Fermionic processes we calculate the entropy density. This can be done either directly using Szeg\\"o's theorem for asymptotic densities of functions of Toeplitz matrices, or through an extension of said theorem to rates of functions, which we present in this article.

Confluence reduction for Markov automata

NARCIS (Netherlands)

Timmer, Mark; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette

Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. Recently, the process algebra MAPA was introduced to efficiently model such systems. As always, the state space explosion threatens the analysability of the models

Confluence Reduction for Markov Automata

NARCIS (Netherlands)

Timmer, Mark; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette; Braberman, Victor; Fribourg, Laurent

Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. Recently, the process algebra MAPA was introduced to efficiently model such systems. As always, the state space explosion threatens the analysability of the models

DISEÑO Y MANIPULACIÓN DE MODELOS OCULTOS DE MARKOV, UTILIZANDO HERRAMIENTAS HTK: UNA TUTORÍA DESIGN AND MANIPULATION OF HIDDEN MARKOV MODELS USING HTK TOOLS: A TUTORIAL

Directory of Open Access Journals (Sweden)

Roberto Carrillo Aguilar

2007-04-01

Full Text Available Este trabajo da a conocer el sistema de desarrollo de software para el diseño y manipulación de modelos ocultos de Markov, denominado HTK. Actualmente, la técnica de modelos ocultos de Markov es la herramienta más efectiva para implementar sistemas reconocedores del habla. HTK está orientado principalmente a ese aspecto. Su arquitectura es robusta y autosuficiente. Permite: la entrada lógica y natural desde un micrófono, dispone de módulos para la conversión A/D, preprocesado y parametrización de la información, posee herramientas para definir y manipular modelos ocultos de Markov, tiene librerías para entrenamiento y manipulación de los modelos ocultos de Markov ya definidos, considera funciones para definir la gramática, y además: Una serie de herramientas adicionales permiten lograr el objetivo final de obtener una hipotética transcripción del habla (conversión voz - texto.This paper presents HTK, a software development platform for the design and management of Hidden Markov Models. Nowadays, the Hidden Markov Models technique is the more effective one to implement voice recognition systems. HTK is mainly oriented to this application. Its architecture is robust and self-sufficient. It allows a natural input from a microphone, it has modules for A/D conversion, it allows pre-processing and parameterization of information, it possesses tools to define and manage the Hidden Markov Models, libraries for training and use the already defined Hidden Markov Models. It has functions to define the grammar and it has additional tools to reach the final objective, to obtain an hypothetical transcription of the talking (voice to text translation.

The Consensus String Problem and the Complexity of Comparing Hidden Markov Models

DEFF Research Database (Denmark)

Lyngsø, Rune Bang; Pedersen, Christian Nørgaard Storm

2002-01-01

The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960s, and has since then been applied to numerous problems, e.g. biological sequence analysis. Most applications of hidden Markov models are based on efficient algorithms for computing...... the probability of generating a given string, or computing the most likely path generating a given string. In this paper we consider the problem of computing the most likely string, or consensus string, generated by a given model, and its implications on the complexity of comparing hidden Markov models. We show...... that computing the consensus string, and approximating its probability within any constant factor, is NP-hard, and that the same holds for the closely related labeling problem for class hidden Markov models. Furthermore, we establish the NP-hardness of comparing two hidden Markov models under the L∞- and L1...

Quantum tomography, phase-space observables and generalized Markov kernels

International Nuclear Information System (INIS)

Pellonpaeae, Juha-Pekka

2009-01-01

We construct a generalized Markov kernel which transforms the observable associated with the homodyne tomography into a covariant phase-space observable with a regular kernel state. Illustrative examples are given in the cases of a 'Schroedinger cat' kernel state and the Cahill-Glauber s-parametrized distributions. Also we consider an example of a kernel state when the generalized Markov kernel cannot be constructed.

Computing continuous-time Markov chains as transformers of unbounded observables

DEFF Research Database (Denmark)

Danos, Vincent; Heindel, Tobias; Garnier, Ilias

2017-01-01

The paper studies continuous-time Markov chains (CTMCs) as transformers of real-valued functions on their state space, considered as generalised predicates and called observables. Markov chains are assumed to take values in a countable state space S; observables f: S → ℝ may be unbounded...

Taking a Closer Look at English Learner Subgroups Whose Achievement Stalls Out. REL West Research Digest

Science.gov (United States)

Regional Educational Laboratory West, 2014

2014-01-01

To figure out better ways to serve their English language learner (ELL) students, the state departments of education in the West Region states of Arizona, Nevada, and Utah, who are members of the English Learner Alliance, asked REL West to help them put together a more detailed picture of two particular groups of K-12 ELL students who seem to…

On a Markov chain roulette-type game

International Nuclear Information System (INIS)

El-Shehawey, M A; El-Shreef, Gh A

2009-01-01

A Markov chain on non-negative integers which arises in a roulette-type game is discussed. The transition probabilities are p 01 = ρ, p Nj = δ Nj , p i,i+W = q, p i,i-1 = p = 1 - q, 1 ≤ W < N, 0 ≤ ρ ≤ 1, N - W < j ≤ N and i = 1, 2, ..., N - W. Using formulae for the determinant of a partitioned matrix, a closed form expression for the solution of the Markov chain roulette-type game is deduced. The present analysis is supported by two mathematical models from tumor growth and war with bargaining

ANALYTIC WORD RECOGNITION WITHOUT SEGMENTATION BASED ON MARKOV RANDOM FIELDS

NARCIS (Netherlands)

Coisy, C.; Belaid, A.

2004-01-01

In this paper, a method for analytic handwritten word recognition based on causal Markov random fields is described. The words models are HMMs where each state corresponds to a letter; each letter is modelled by a NSHP­HMM (Markov field). Global models are build dynamically, and used for recognition

A Markov decision model for optimising economic production lot size ...

African Journals Online (AJOL)

Adopting such a Markov decision process approach, the states of a Markov chain represent possible states of demand. The decision of whether or not to produce additional inventory units is made using dynamic programming. This approach demonstrates the existence of an optimal state-dependent EPL size, and produces ...

Exact goodness-of-fit tests for Markov chains.

Science.gov (United States)

Besag, J; Mondal, D

2013-06-01

Goodness-of-fit tests are useful in assessing whether a statistical model is consistent with available data. However, the usual χ² asymptotics often fail, either because of the paucity of the data or because a nonstandard test statistic is of interest. In this article, we describe exact goodness-of-fit tests for first- and higher order Markov chains, with particular attention given to time-reversible ones. The tests are obtained by conditioning on the sufficient statistics for the transition probabilities and are implemented by simple Monte Carlo sampling or by Markov chain Monte Carlo. They apply both to single and to multiple sequences and allow a free choice of test statistic. Three examples are given. The first concerns multiple sequences of dry and wet January days for the years 1948-1983 at Snoqualmie Falls, Washington State, and suggests that standard analysis may be misleading. The second one is for a four-state DNA sequence and lends support to the original conclusion that a second-order Markov chain provides an adequate fit to the data. The last one is six-state atomistic data arising in molecular conformational dynamics simulation of solvated alanine dipeptide and points to strong evidence against a first-order reversible Markov chain at 6 picosecond time steps. © 2013, The International Biometric Society.

Real and hypothetical endowment effects when exchanging lottery tickets: Is regret a better explanation than loss aversion?

Science.gov (United States)

Kogler, Christoph; Kühberger, Anton; Gilhofer, Rainer

2013-08-01

The endowment effect is the finding that possession of an item adds to its value. We introduce a new procedure for testing this effect: participants are divided into two groups. Possession group participants inspect a numbered lottery ticket and know it is theirs, while inspection group participants only inspect a lottery ticket without being endowed with it. Subsequently participants choose between playing the lottery with this (possessed or inspected) ticket, or exchanging it for another one. Our procedure tests for the effect of endowment while controlling for the influence of transaction costs as well as for inspection effects and the influence of bargaining roles (buyer vs. seller), which often afflict experimentation with the endowment effect. In a real setting, tickets in possession were valued significantly higher than inspected tickets. Contrary to some findings in the literature participants also correctly predicted these valuation differences in a hypothetical situation, both for themselves as well as for others. Furthermore, our results suggest that regret rather than loss aversion may be the source of the endowment effect in an experimental setting using lottery tickets. Applying our procedure to a setting employing riskless objects in form of mugs revealed rather ambiguous results, thus emphasizing that the role of regret might be less prominent in non-lottery settings.

WebQuest Learning as Perceived by Higher-Education Learners

Science.gov (United States)

Zheng, Robert; Stucky, Bradd; McAlack, Matt; Menchaca, Mike; Stoddart, Sue

2005-01-01

The WebQuest as an inquiry-oriented approach in web learning has gained considerable attention from educators and has been integrated widely into curricula in K-12 and higher education. It is considered to be an effective way to organize chaotic internet resources and help learners gain new knowledge through a guided learning environment.…

Learner-to-learner visual acuity screening: A solution for early ...

African Journals Online (AJOL)

The National School Health Policy guidelines (2002) stipulate that primary school learners should have their vision, speech, hearing, mental health, teeth, ... This project created greater awareness among learners, parents and teachers ...

Evaluation of Jefferies' level population ratios, and generalization of Seaton's cascade matrix, by a Markov-chain method

International Nuclear Information System (INIS)

Kastner, S.O.

1980-01-01

Closed expressions are obtained for the conditional probabilities qsub(i)sub(j)sub(,)sub(k) required in evaluating particular ratios of atomic level populations, using a Markov-chain representation of the system of levels. The total transition probability between two arbitrary levels is also evaluated and its relation to population ratios is clarified. It is shown that Seaton's cascade matrix is a subset of the total transition probability matrix. (orig.)

MARKOV CHAIN PORTFOLIO LIQUIDITY OPTIMIZATION MODEL

Directory of Open Access Journals (Sweden)

Eder Oliveira Abensur

2014-05-01

Full Text Available The international financial crisis of September 2008 and May 2010 showed the importance of liquidity as an attribute to be considered in portfolio decisions. This study proposes an optimization model based on available public data, using Markov chain and Genetic Algorithms concepts as it considers the classic duality of risk versus return and incorporating liquidity costs. The work intends to propose a multi-criterion non-linear optimization model using liquidity based on a Markov chain. The non-linear model was tested using Genetic Algorithms with twenty five Brazilian stocks from 2007 to 2009. The results suggest that this is an innovative development methodology and useful for developing an efficient and realistic financial portfolio, as it considers many attributes such as risk, return and liquidity.

Transportation and concentration inequalities for bifurcating Markov chains

DEFF Research Database (Denmark)

Penda, S. Valère Bitseki; Escobar-Bach, Mikael; Guillin, Arnaud

2017-01-01

We investigate the transportation inequality for bifurcating Markov chains which are a class of processes indexed by a regular binary tree. Fitting well models like cell growth when each individual gives birth to exactly two offsprings, we use transportation inequalities to provide useful...... concentration inequalities.We also study deviation inequalities for the empirical means under relaxed assumptions on the Wasserstein contraction for the Markov kernels. Applications to bifurcating nonlinear autoregressive processes are considered for point-wise estimates of the non-linear autoregressive...

Using multi-state markov models to identify credit card risk

Directory of Open Access Journals (Sweden)

Daniel Evangelista Régis

2016-06-01

Full Text Available Abstract The main interest of this work is to analyze the application of multi-state Markov models to evaluate credit card risk by investigating the characteristics of different state transitions in client-institution relationships over time, thereby generating score models for various purposes. We also used logistic regression models to compare the results with those obtained using multi-state Markov models. The models were applied to an actual database of a Brazilian financial institution. In this application, multi-state Markov models performed better than logistic regression models in predicting default risk, and logistic regression models performed better in predicting cancellation risk.

On almost-periodic points of a topological Markov chain

International Nuclear Information System (INIS)

Bogatyi, Semeon A; Redkozubov, Vadim V

2012-01-01

We prove that a transitive topological Markov chain has almost-periodic points of all D-periods. Moreover, every D-period is realized by continuously many distinct minimal sets. We give a simple constructive proof of the result which asserts that any transitive topological Markov chain has periodic points of almost all periods, and study the structure of the finite set of positive integers that are not periods.

Hidden Markov Model Application to Transfer The Trader Online Forex Brokers

Directory of Open Access Journals (Sweden)

Farida Suharleni

2012-05-01

Full Text Available Hidden Markov Model is elaboration of Markov chain, which is applicable to cases that can’t directly observe. In this research, Hidden Markov Model is used to know trader’s transition to broker forex online. In Hidden Markov Model, observed state is observable part and hidden state is hidden part. Hidden Markov Model allows modeling system that contains interrelated observed state and hidden state. As observed state in trader’s transition to broker forex online is category 1, category 2, category 3, category 4, category 5 by condition of every broker forex online, whereas as hidden state is broker forex online Marketiva, Masterforex, Instaforex, FBS and Others. First step on application of Hidden Markov Model in this research is making construction model by making a probability of transition matrix (A from every broker forex online. Next step is making a probability of observation matrix (B by making conditional probability of five categories, that is category 1, category 2, category 3, category 4, category 5 by condition of every broker forex online and also need to determine an initial state probability (π from every broker forex online. The last step is using Viterbi algorithm to find hidden state sequences that is broker forex online sequences which is the most possible based on model and observed state that is the five categories. Application of Hidden Markov Model is done by making program with Viterbi algorithm using Delphi 7.0 software with observed state based on simulation data. Example: By the number of observation T = 5 and observed state sequences O = (2,4,3,5,1 is found hidden state sequences which the most possible with observed state O as following : where X1 = FBS, X2 = Masterforex, X3 = Marketiva, X4 = Others, and X5 = Instaforex.

Markov Chain Models for the Stochastic Modeling of Pitting Corrosion

Directory of Open Access Journals (Sweden)

A. Valor

2013-01-01

Full Text Available The stochastic nature of pitting corrosion of metallic structures has been widely recognized. It is assumed that this kind of deterioration retains no memory of the past, so only the current state of the damage influences its future development. This characteristic allows pitting corrosion to be categorized as a Markov process. In this paper, two different models of pitting corrosion, developed using Markov chains, are presented. Firstly, a continuous-time, nonhomogeneous linear growth (pure birth Markov process is used to model external pitting corrosion in underground pipelines. A closed-form solution of the system of Kolmogorov's forward equations is used to describe the transition probability function in a discrete pit depth space. The transition probability function is identified by correlating the stochastic pit depth mean with the empirical deterministic mean. In the second model, the distribution of maximum pit depths in a pitting experiment is successfully modeled after the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time is simulated as the realization of a Weibull process. Pit growth is simulated using a nonhomogeneous Markov process. An analytical solution of Kolmogorov's system of equations is also found for the transition probabilities from the first Markov state. Extreme value statistics is employed to find the distribution of maximum pit depths.

Adaptive Partially Hidden Markov Models

DEFF Research Database (Denmark)

Forchhammer, Søren Otto; Rasmussen, Tage

1996-01-01

Partially Hidden Markov Models (PHMM) have recently been introduced. The transition and emission probabilities are conditioned on the past. In this report, the PHMM is extended with a multiple token version. The different versions of the PHMM are applied to bi-level image coding....

Gold price effect on stock market: A Markov switching vector error correction approach

Science.gov (United States)

Wai, Phoong Seuk; Ismail, Mohd Tahir; Kun, Sek Siok

2014-06-01

Gold is a popular precious metal where the demand is driven not only for practical use but also as a popular investments commodity. While stock market represents a country growth, thus gold price effect on stock market behavior as interest in the study. Markov Switching Vector Error Correction Models are applied to analysis the relationship between gold price and stock market changes since real financial data always exhibit regime switching, jumps or missing data through time. Besides, there are numerous specifications of Markov Switching Vector Error Correction Models and this paper will compare the intercept adjusted Markov Switching Vector Error Correction Model and intercept adjusted heteroskedasticity Markov Switching Vector Error Correction Model to determine the best model representation in capturing the transition of the time series. Results have shown that gold price has a positive relationship with Malaysia, Thailand and Indonesia stock market and a two regime intercept adjusted heteroskedasticity Markov Switching Vector Error Correction Model is able to provide the more significance and reliable result compare to intercept adjusted Markov Switching Vector Error Correction Models.

The semi-Markov process. Generalizations and calculation rules for application in the analysis of systems

International Nuclear Information System (INIS)

Hirschmann, H.

1983-06-01

The consequences of the basic assumptions of the semi-Markov process as defined from a homogeneous renewal process with a stationary Markov condition are reviewed. The notion of the semi-Markov process is generalized by its redefinition from a nonstationary Markov renewal process. For both the nongeneralized and the generalized case a representation of the first order conditional state probabilities is derived in terms of the transition probabilities of the Markov renewal process. Some useful calculation rules (regeneration rules) are derived for the conditional state probabilities of the semi-Markov process. Compared to the semi-Markov process in its usual definition the generalized process allows the analysis of a larger class of systems. For instance systems with arbitrarily distributed lifetimes of their components can be described. There is also a chance to describe systems which are modified during time by forces or manipulations from outside. (Auth.)

The explicit form of the rate function for semi-Markov processes and its contractions

Science.gov (United States)

Sughiyama, Yuki; Kobayashi, Testuya J.

2018-03-01

We derive the explicit form of the rate function for semi-Markov processes. Here, the ‘random time change trick’ plays an essential role. Also, by exploiting the contraction principle of large deviation theory to the explicit form, we show that the fluctuation theorem (Gallavotti-Cohen symmetry) holds for semi-Markov cases. Furthermore, we elucidate that our rate function is an extension of the level 2.5 rate function for Markov processes to semi-Markov cases.

Constructing Dynamic Event Trees from Markov Models

International Nuclear Information System (INIS)

Paolo Bucci; Jason Kirschenbaum; Tunc Aldemir; Curtis Smith; Ted Wood

2006-01-01

In the probabilistic risk assessment (PRA) of process plants, Markov models can be used to model accurately the complex dynamic interactions between plant physical process variables (e.g., temperature, pressure, etc.) and the instrumentation and control system that monitors and manages the process. One limitation of this approach that has prevented its use in nuclear power plant PRAs is the difficulty of integrating the results of a Markov analysis into an existing PRA. In this paper, we explore a new approach to the generation of failure scenarios and their compilation into dynamic event trees from a Markov model of the system. These event trees can be integrated into an existing PRA using software tools such as SAPHIRE. To implement our approach, we first construct a discrete-time Markov chain modeling the system of interest by: (a) partitioning the process variable state space into magnitude intervals (cells), (b) using analytical equations or a system simulator to determine the transition probabilities between the cells through the cell-to-cell mapping technique, and, (c) using given failure/repair data for all the components of interest. The Markov transition matrix thus generated can be thought of as a process model describing the stochastic dynamic behavior of the finite-state system. We can therefore search the state space starting from a set of initial states to explore all possible paths to failure (scenarios) with associated probabilities. We can also construct event trees of arbitrary depth by tracing paths from a chosen initiating event and recording the following events while keeping track of the probabilities associated with each branch in the tree. As an example of our approach, we use the simple level control system often used as benchmark in the literature with one process variable (liquid level in a tank), and three control units: a drain unit and two supply units. Each unit includes a separate level sensor to observe the liquid level in the tank

A Markov reward model checker

NARCIS (Netherlands)

Katoen, Joost P.; Maneesh Khattri, M.; Zapreev, I.S.; Zapreev, I.S.

2005-01-01

This short tool paper introduces MRMC, a model checker for discrete-time and continuous-time Markov reward models. It supports reward extensions of PCTL and CSL, and allows for the automated verification of properties concerning long-run and instantaneous rewards as well as cumulative rewards. In

Markov chains and mixing times

CERN Document Server

Levin, David A

2017-01-01

Markov Chains and Mixing Times is a magical book, managing to be both friendly and deep. It gently introduces probabilistic techniques so that an outsider can follow. At the same time, it is the first book covering the geometric theory of Markov chains and has much that will be new to experts. It is certainly THE book that I will use to teach from. I recommend it to all comers, an amazing achievement. -Persi Diaconis, Mary V. Sunseri Professor of Statistics and Mathematics, Stanford University Mixing times are an active research topic within many fields from statistical physics to the theory of algorithms, as well as having intrinsic interest within mathematical probability and exploiting discrete analogs of important geometry concepts. The first edition became an instant classic, being accessible to advanced undergraduates and yet bringing readers close to current research frontiers. This second edition adds chapters on monotone chains, the exclusion process and hitting time parameters. Having both exercises...

Monte Carlo methods for the reliability analysis of Markov systems

International Nuclear Information System (INIS)

Buslik, A.J.

1985-01-01

This paper presents Monte Carlo methods for the reliability analysis of Markov systems. Markov models are useful in treating dependencies between components. The present paper shows how the adjoint Monte Carlo method for the continuous time Markov process can be derived from the method for the discrete-time Markov process by a limiting process. The straightforward extensions to the treatment of mean unavailability (over a time interval) are given. System unavailabilities can also be estimated; this is done by making the system failed states absorbing, and not permitting repair from them. A forward Monte Carlo method is presented in which the weighting functions are related to the adjoint function. In particular, if the exact adjoint function is known then weighting factors can be constructed such that the exact answer can be obtained with a single Monte Carlo trial. Of course, if the exact adjoint function is known, there is no need to perform the Monte Carlo calculation. However, the formulation is useful since it gives insight into choices of the weight factors which will reduce the variance of the estimator

Applying Markov Chains for NDVI Time Series Forecasting of Latvian Regions

Directory of Open Access Journals (Sweden)

Stepchenko Arthur

2015-12-01

Full Text Available Time series of earth observation based estimates of vegetation inform about variations in vegetation at the scale of Latvia. A vegetation index is an indicator that describes the amount of chlorophyll (the green mass and shows the relative density and health of vegetation. NDVI index is an important variable for vegetation forecasting and management of various problems, such as climate change monitoring, energy usage monitoring, managing the consumption of natural resources, agricultural productivity monitoring, drought monitoring and forest fire detection. In this paper, we make a one-step-ahead prediction of 7-daily time series of NDVI index using Markov chains. The choice of a Markov chain is due to the fact that a Markov chain is a sequence of random variables where each variable is located in some state. And a Markov chain contains probabilities of moving from one state to other.

Tornadoes and related damage costs: statistical modeling with a semi-Markov approach

OpenAIRE

Corini, Chiara; D'Amico, Guglielmo; Petroni, Filippo; Prattico, Flavio; Manca, Raimondo

2015-01-01

We propose a statistical approach to tornadoes modeling for predicting and simulating occurrences of tornadoes and accumulated cost distributions over a time interval. This is achieved by modeling the tornadoes intensity, measured with the Fujita scale, as a stochastic process. Since the Fujita scale divides tornadoes intensity into six states, it is possible to model the tornadoes intensity by using Markov and semi-Markov models. We demonstrate that the semi-Markov approach is able to reprod...

Hidden Markov processes theory and applications to biology

CERN Document Server

Vidyasagar, M

2014-01-01

This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. The book starts from first principles, so that no previous knowledge of probability is necessary. However, the work is rigorous and mathematical, making it useful to engineers and mathematicians, even those not interested in biological applications. A range of exercises is provided, including drills to familiarize the reader with concepts and more advanced problems that require deep thinking about the theory. Biological applications are t

Application of Hidden Markov Models in Biomolecular Simulations.

Science.gov (United States)

Shukla, Saurabh; Shamsi, Zahra; Moffett, Alexander S; Selvam, Balaji; Shukla, Diwakar

2017-01-01

Hidden Markov models (HMMs) provide a framework to analyze large trajectories of biomolecular simulation datasets. HMMs decompose the conformational space of a biological molecule into finite number of states that interconvert among each other with certain rates. HMMs simplify long timescale trajectories for human comprehension, and allow comparison of simulations with experimental data. In this chapter, we provide an overview of building HMMs for analyzing bimolecular simulation datasets. We demonstrate the procedure for building a Hidden Markov model for Met-enkephalin peptide simulation dataset and compare the timescales of the process.

Bisimulation on Markov Processes over Arbitrary Measurable Spaces

DEFF Research Database (Denmark)

Bacci, Giorgio; Bacci, Giovanni; Larsen, Kim Guldstrand

2014-01-01

We introduce a notion of bisimulation on labelled Markov Processes over generic measurable spaces in terms of arbitrary binary relations. Our notion of bisimulation is proven to coincide with the coalgebraic definition of Aczel and Mendler in terms of the Giry functor, which associates with a mea......We introduce a notion of bisimulation on labelled Markov Processes over generic measurable spaces in terms of arbitrary binary relations. Our notion of bisimulation is proven to coincide with the coalgebraic definition of Aczel and Mendler in terms of the Giry functor, which associates...

Detecting Faults By Use Of Hidden Markov Models

Science.gov (United States)

Smyth, Padhraic J.

1995-01-01

Frequency of false alarms reduced. Faults in complicated dynamic system (e.g., antenna-aiming system, telecommunication network, or human heart) detected automatically by method of automated, continuous monitoring. Obtains time-series data by sampling multiple sensor outputs at discrete intervals of t and processes data via algorithm determining whether system in normal or faulty state. Algorithm implements, among other things, hidden first-order temporal Markov model of states of system. Mathematical model of dynamics of system not needed. Present method is "prior" method mentioned in "Improved Hidden-Markov-Model Method of Detecting Faults" (NPO-18982).

Learner's Passport

Directory of Open Access Journals (Sweden)

Bogdan Jug

1996-12-01

Full Text Available For the first time learner's passport was pre­ sented at the international conference on permanent education, taking place in Rome in December 1994. This document is not meant for students only but for the entire population. It should contain notes on any format education, additional education, working experiences, cultural activities, sport results, awards, prizes and recommen­ dations. The mission of learner's passport is to gather all documents in one place, a handy book­ let which gives one an overall view over his/her achievements. It should help personnel departments in choosing the right person for a certain job as well as indirectly stimul ate additional activities of the learner's passport holder.

A Markov Chain Estimator of Multivariate Volatility from High Frequency Data

DEFF Research Database (Denmark)

Hansen, Peter Reinhard; Horel, Guillaume; Lunde, Asger

We introduce a multivariate estimator of financial volatility that is based on the theory of Markov chains. The Markov chain framework takes advantage of the discreteness of high-frequency returns. We study the finite sample properties of the estimation in a simulation study and apply...

Descriptive and predictive evaluation of high resolution Markov chain precipitation models

DEFF Research Database (Denmark)

Sørup, Hjalte Jomo Danielsen; Madsen, Henrik; Arnbjerg-Nielsen, Karsten

2012-01-01

A time series of tipping bucket recordings of very high temporal and volumetric resolution precipitation is modelled using Markov chain models. Both first and second‐order Markov models as well as seasonal and diurnal models are investigated and evaluated using likelihood based techniques. The fi...

Reliability estimation of semi-Markov systems: a case study

International Nuclear Information System (INIS)

Ouhbi, Brahim; Limnios, Nikolaos

1997-01-01

In this article, we are concerned with the estimation of the reliability and the availability of a turbo-generator rotor using a set of data observed in a real engineering situation provided by Electricite De France (EDF). The rotor is modeled by a semi-Markov process, which is used to estimate the rotor's reliability and availability. To do this, we present a method for estimating the semi-Markov kernel from a censored data

Markov Chain Monte Carlo

Indian Academy of Sciences (India)

be obtained as a limiting value of a sample path of a suitable ... makes a mathematical model of chance and deals with the problem by .... Is the Markov chain aperiodic? It is! Here is how you can see it. Suppose that after you do the cut, you hold the top half in your right hand, and the bottom half in your left. Then there.

Visual event-related potential studies supporting the validity of VARK learning styles' visual and read/write learners.

Science.gov (United States)

Thepsatitporn, Sarawin; Pichitpornchai, Chailerd

2016-06-01

The validity of learning styles needs supports of additional objective evidence. The identification of learning styles using subjective evidence from VARK questionnaires (where V is visual, A is auditory, R is read/write, and K is kinesthetic) combined with objective evidence from visual event-related potential (vERP) studies has never been investigated. It is questionable whether picture superiority effects exist in V learners and R learners. Thus, the present study aimed to investigate whether vERP could show the relationship between vERP components and VARK learning styles and to identify the existence of picture superiority effects in V learners and R learners. Thirty medical students (15 V learners and 15 R learners) performed recognition tasks with vERP and an intermediate-term memory (ITM) test. The results of within-group comparisons showed that pictures elicited larger P200 amplitudes than words at the occipital 2 site (P < 0.05) in V learners and at the occipital 1 and 2 sites (P < 0.05) in R learners. The between-groups comparison showed that P200 amplitudes elicited by pictures in V learners were larger than those of R learners at the parietal 4 site (P < 0.05). The ITM test result showed that a picture set showed distinctively more correct responses than that of a word set for both V learners (P < 0.001) and R learners (P < 0.01). In conclusion, the result indicated that the P200 amplitude at the parietal 4 site could be used to objectively distinguish V learners from R learners. A lateralization existed to the right brain (occipital 2 site) in V learners. The ITM test demonstrated the existence of picture superiority effects in both learners. The results revealed the first objective electrophysiological evidence partially supporting the validity of the subjective psychological VARK questionnaire study. Copyright © 2016 The American Physiological Society.

Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains

Directory of Open Access Journals (Sweden)

Behrouz Fathi-Vajargah

2014-01-01

Full Text Available This paper presents a novel fuzzy enhancement technique using simulated ergodic fuzzy Markov chains for low contrast brain magnetic resonance imaging (MRI. The fuzzy image contrast enhancement is proposed by weighted fuzzy expected value. The membership values are then modified to enhance the image using ergodic fuzzy Markov chains. The qualitative performance of the proposed method is compared to another method in which ergodic fuzzy Markov chains are not considered. The proposed method produces better quality image.

failure analysis of a uav flight control system using markov analysis

African Journals Online (AJOL)

eobe

2016-01-01

Jan 1, 2016 ... Tree Analysis (FTA), Dependence Diagram Analysis. (DDA) and Markov Analysis (MA) are the most widely-used methods of probabilistic safety and reliability analysis for airborne system [1]. Fault trees analysis is a backward failure searching ..... [4] Christopher Dabrowski and Fern Hunt Markov Chain.

Minimizing the regrets of long-term urban floodplain management decisions under deeply uncertain climate change

Science.gov (United States)

Hecht, J. S.; Kirshen, P. H.; Vogel, R. M.

2016-12-01

Making long-term floodplain management decisions under uncertain climate change is a major urban planning challenge of the 21stcentury. To support these efforts, we introduce a screening-level optimization model that identifies adaptation portfolios by minimizing the regrets associated with their flood-control and damage costs under different climate change trajectories that are deeply uncertain, i.e. have probabilities that cannot be specified plausibly. This mixed integer program explicitly considers the coupled damage-reduction impacts of different floodwall designs and property-scale investments (first-floor elevation, wet floodproofing of basements, permanent retreat and insurance), recommends implementation schedules, and assesses impacts to stakeholders residing in three types of homes. An application to a stylized municipality illuminates many nonlinear system dynamics stemming from large fixed capital costs, infrastructure design thresholds, and discharge-depth-damage relationships. If stakeholders tolerate mild damage, floodwalls that fully protect a community from large design events are less cost-effective than portfolios featuring both smaller floodwalls and property-scale measures. Potential losses of property tax revenue from permanent retreat motivate municipal property-tax initiatives for adaptation financing. Yet, insurance incentives for first-floor elevation may discourage locally financed floodwalls, in turn making lower-income residents more vulnerable to severe flooding. A budget constraint analysis underscores the benefits of flexible floodwall designs with low incremental expansion costs while near-optimal solutions demonstrate the scheduling flexibility of many property-scale measures. Finally, an equity analysis shows the importance of evaluating the overpayment and under-design regrets of recommended adaptation portfolios for each stakeholder and contrasts them to single-scenario model results.

Entanglement revival can occur only when the system-environment state is not a Markov state

Science.gov (United States)

Sargolzahi, Iman

2018-06-01

Markov states have been defined for tripartite quantum systems. In this paper, we generalize the definition of the Markov states to arbitrary multipartite case and find the general structure of an important subset of them, which we will call strong Markov states. In addition, we focus on an important property of the Markov states: If the initial state of the whole system-environment is a Markov state, then each localized dynamics of the whole system-environment reduces to a localized subdynamics of the system. This provides us a necessary condition for entanglement revival in an open quantum system: Entanglement revival can occur only when the system-environment state is not a Markov state. To illustrate (a part of) our results, we consider the case that the environment is modeled as classical. In this case, though the correlation between the system and the environment remains classical during the evolution, the change of the state of the system-environment, from its initial Markov state to a state which is not a Markov one, leads to the entanglement revival in the system. This shows that the non-Markovianity of a state is not equivalent to the existence of non-classical correlation in it, in general.

An Approach of Diagnosis Based On The Hidden Markov Chains Model

Directory of Open Access Journals (Sweden)

Karim Bouamrane

2008-07-01

Full Text Available Diagnosis is a key element in industrial system maintenance process performance. A diagnosis tool is proposed allowing the maintenance operators capitalizing on the knowledge of their trade and subdividing it for better performance improvement and intervention effectiveness within the maintenance process service. The Tool is based on the Markov Chain Model and more precisely the Hidden Markov Chains (HMC which has the system failures determination advantage, taking into account the causal relations, stochastic context modeling of their dynamics and providing a relevant diagnosis help by their ability of dubious information use. Since the FMEA method is a well adapted artificial intelligence field, the modeling with Markov Chains is carried out with its assistance. Recently, a dynamic programming recursive algorithm, called 'Viterbi Algorithm', is being used in the Hidden Markov Chains field. This algorithm provides as input to the HMC a set of system observed effects and generates at exit the various causes having caused the loss from one or several system functions.

Analysis and design of Markov jump systems with complex transition probabilities

CERN Document Server

Zhang, Lixian; Shi, Peng; Zhu, Yanzheng

2016-01-01

The book addresses the control issues such as stability analysis, control synthesis and filter design of Markov jump systems with the above three types of TPs, and thus is mainly divided into three parts. Part I studies the Markov jump systems with partially unknown TPs. Different methodologies with different conservatism for the basic stability and stabilization problems are developed and compared. Then the problems of state estimation, the control of systems with time-varying delays, the case involved with both partially unknown TPs and uncertain TPs in a composite way are also tackled. Part II deals with the Markov jump systems with piecewise homogeneous TPs. Methodologies that can effectively handle control problems in the scenario are developed, including the one coping with the asynchronous switching phenomenon between the currently activated system mode and the controller/filter to be designed. Part III focuses on the Markov jump systems with memory TPs. The concept of σ-mean square stability is propo...

Markov chain solution of photon multiple scattering through turbid slabs.

Science.gov (United States)

Lin, Ying; Northrop, William F; Li, Xuesong

2016-11-14

This work introduces a Markov Chain solution to model photon multiple scattering through turbid slabs via anisotropic scattering process, i.e., Mie scattering. Results show that the proposed Markov Chain model agree with commonly used Monte Carlo simulation for various mediums such as medium with non-uniform phase functions and absorbing medium. The proposed Markov Chain solution method successfully converts the complex multiple scattering problem with practical phase functions into a matrix form and solves transmitted/reflected photon angular distributions by matrix multiplications. Such characteristics would potentially allow practical inversions by matrix manipulation or stochastic algorithms where widely applied stochastic methods such as Monte Carlo simulations usually fail, and thus enable practical diagnostics reconstructions such as medical diagnosis, spray analysis, and atmosphere sciences.

The spectral method and ergodic theorems for general Markov chains

International Nuclear Information System (INIS)

Nagaev, S V

2015-01-01

We study the ergodic properties of Markov chains with an arbitrary state space and prove a geometric ergodic theorem. The method of the proof is new: it may be described as an operator method. Our main result is an ergodic theorem for Harris-Markov chains in the case when the return time to some fixed set has finite expectation. Our conditions for the transition function are more general than those used by Athreya-Ney and Nummelin. Unlike them, we impose restrictions not on the original transition function but on the transition function of an embedded Markov chain constructed from the return times to the fixed set mentioned above. The proof uses the spectral theory of linear operators on a Banach space

Influence of credit scoring on the dynamics of Markov chain

Science.gov (United States)

Galina, Timofeeva

2015-11-01

Markov processes are widely used to model the dynamics of a credit portfolio and forecast the portfolio risk and profitability. In the Markov chain model the loan portfolio is divided into several groups with different quality, which determined by presence of indebtedness and its terms. It is proposed that dynamics of portfolio shares is described by a multistage controlled system. The article outlines mathematical formalization of controls which reflect the actions of the bank's management in order to improve the loan portfolio quality. The most important control is the organization of approval procedure of loan applications. The credit scoring is studied as a control affecting to the dynamic system. Different formalizations of "good" and "bad" consumers are proposed in connection with the Markov chain model.

Prediction of pipeline corrosion rate based on grey Markov models

International Nuclear Information System (INIS)

Chen Yonghong; Zhang Dafa; Peng Guichu; Wang Yuemin

2009-01-01

Based on the model that combined by grey model and Markov model, the prediction of corrosion rate of nuclear power pipeline was studied. Works were done to improve the grey model, and the optimization unbiased grey model was obtained. This new model was used to predict the tendency of corrosion rate, and the Markov model was used to predict the residual errors. In order to improve the prediction precision, rolling operation method was used in these prediction processes. The results indicate that the improvement to the grey model is effective and the prediction precision of the new model combined by the optimization unbiased grey model and Markov model is better, and the use of rolling operation method may improve the prediction precision further. (authors)

On the entropy of a hidden Markov process.

Science.gov (United States)

Jacquet, Philippe; Seroussi, Gadiel; Szpankowski, Wojciech

2008-05-01

We study the entropy rate of a hidden Markov process (HMP) defined by observing the output of a binary symmetric channel whose input is a first-order binary Markov process. Despite the simplicity of the models involved, the characterization of this entropy is a long standing open problem. By presenting the probability of a sequence under the model as a product of random matrices, one can see that the entropy rate sought is equal to a top Lyapunov exponent of the product. This offers an explanation for the elusiveness of explicit expressions for the HMP entropy rate, as Lyapunov exponents are notoriously difficult to compute. Consequently, we focus on asymptotic estimates, and apply the same product of random matrices to derive an explicit expression for a Taylor approximation of the entropy rate with respect to the parameter of the binary symmetric channel. The accuracy of the approximation is validated against empirical simulation results. We also extend our results to higher-order Markov processes and to Rényi entropies of any order.

Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

Czech Academy of Sciences Publication Activity Database

Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

2009-01-01

Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

A Probabilistic Short-Term Water Demand Forecasting Model Based on the Markov Chain

Directory of Open Access Journals (Sweden)

Francesca Gagliardi

2017-07-01

Full Text Available This paper proposes a short-term water demand forecasting method based on the use of the Markov chain. This method provides estimates of future demands by calculating probabilities that the future demand value will fall within pre-assigned intervals covering the expected total variability. More specifically, two models based on homogeneous and non-homogeneous Markov chains were developed and presented. These models, together with two benchmark models (based on artificial neural network and naïve methods, were applied to three real-life case studies for the purpose of forecasting the respective water demands from 1 to 24 h ahead. The results obtained show that the model based on a homogeneous Markov chain provides more accurate short-term forecasts than the one based on a non-homogeneous Markov chain, which is in line with the artificial neural network model. Both Markov chain models enable probabilistic information regarding the stochastic demand forecast to be easily obtained.

Mapping absorption processes onto a Markov chain, conserving the mean first passage time

International Nuclear Information System (INIS)

Biswas, Katja

2013-01-01

The dynamics of a multidimensional system is projected onto a discrete state master equation using the transition rates W(k → k′; t, t + dt) between a set of states {k} represented by the regions {ζ k } in phase or discrete state space. Depending on the dynamics Γ i (t) of the original process and the choice of ζ k , the discretized process can be Markovian or non-Markovian. For absorption processes, it is shown that irrespective of these properties of the projection, a master equation with time-independent transition rates W-bar (k→k ' ) can be obtained, which conserves the total occupation time of the partitions of the phase or discrete state space of the original process. An expression for the transition probabilities p-bar (k ' |k) is derived based on either time-discrete measurements {t i } with variable time stepping Δ (i+1)i = t i+1 − t i or the theoretical knowledge at continuous times t. This allows computational methods of absorbing Markov chains to be used to obtain the mean first passage time (MFPT) of the system. To illustrate this approach, the procedure is applied to obtain the MFPT for the overdamped Brownian motion of particles subject to a system with dichotomous noise and the escape from an entropic barrier. The high accuracy of the simulation results confirms with the theory. (paper)

Road maintenance optimization through a discrete-time semi-Markov decision process

International Nuclear Information System (INIS)

Zhang Xueqing; Gao Hui

2012-01-01

Optimization models are necessary for efficient and cost-effective maintenance of a road network. In this regard, road deterioration is commonly modeled as a discrete-time Markov process such that an optimal maintenance policy can be obtained based on the Markov decision process, or as a renewal process such that an optimal maintenance policy can be obtained based on the renewal theory. However, the discrete-time Markov process cannot capture the real time at which the state transits while the renewal process considers only one state and one maintenance action. In this paper, road deterioration is modeled as a semi-Markov process in which the state transition has the Markov property and the holding time in each state is assumed to follow a discrete Weibull distribution. Based on this semi-Markov process, linear programming models are formulated for both infinite and finite planning horizons in order to derive optimal maintenance policies to minimize the life-cycle cost of a road network. A hypothetical road network is used to illustrate the application of the proposed optimization models. The results indicate that these linear programming models are practical for the maintenance of a road network having a large number of road segments and that they are convenient to incorporate various constraints on the decision process, for example, performance requirements and available budgets. Although the optimal maintenance policies obtained for the road network are randomized stationary policies, the extent of this randomness in decision making is limited. The maintenance actions are deterministic for most states and the randomness in selecting actions occurs only for a few states.

Modeling nonhomogeneous Markov processes via time transformation.

Science.gov (United States)

Hubbard, R A; Inoue, L Y T; Fann, J R

2008-09-01

Longitudinal studies are a powerful tool for characterizing the course of chronic disease. These studies are usually carried out with subjects observed at periodic visits giving rise to panel data. Under this observation scheme the exact times of disease state transitions and sequence of disease states visited are unknown and Markov process models are often used to describe disease progression. Most applications of Markov process models rely on the assumption of time homogeneity, that is, that the transition rates are constant over time. This assumption is not satisfied when transition rates depend on time from the process origin. However, limited statistical tools are available for dealing with nonhomogeneity. We propose models in which the time scale of a nonhomogeneous Markov process is transformed to an operational time scale on which the process is homogeneous. We develop a method for jointly estimating the time transformation and the transition intensity matrix for the time transformed homogeneous process. We assess maximum likelihood estimation using the Fisher scoring algorithm via simulation studies and compare performance of our method to homogeneous and piecewise homogeneous models. We apply our methodology to a study of delirium progression in a cohort of stem cell transplantation recipients and show that our method identifies temporal trends in delirium incidence and recovery.

Markov Decision Processes in Practice

NARCIS (Netherlands)

Boucherie, Richardus J.; van Dijk, N.M.

2017-01-01

It is over 30 years ago since D.J. White started his series of surveys on practical applications of Markov decision processes (MDP), over 20 years after the phenomenal book by Martin Puterman on the theory of MDP, and over 10 years since Eugene A. Feinberg and Adam Shwartz published their Handbook

Operations and support cost modeling using Markov chains

Science.gov (United States)

Unal, Resit

1989-01-01

Systems for future missions will be selected with life cycle costs (LCC) as a primary evaluation criterion. This reflects the current realization that only systems which are considered affordable will be built in the future due to the national budget constaints. Such an environment calls for innovative cost modeling techniques which address all of the phases a space system goes through during its life cycle, namely: design and development, fabrication, operations and support; and retirement. A significant portion of the LCC for reusable systems are generated during the operations and support phase (OS). Typically, OS costs can account for 60 to 80 percent of the total LCC. Clearly, OS costs are wholly determined or at least strongly influenced by decisions made during the design and development phases of the project. As a result OS costs need to be considered and estimated early in the conceptual phase. To be effective, an OS cost estimating model needs to account for actual instead of ideal processes by associating cost elements with probabilities. One approach that may be suitable for OS cost modeling is the use of the Markov Chain Process. Markov chains are an important method of probabilistic analysis for operations research analysts but they are rarely used for life cycle cost analysis. This research effort evaluates the use of Markov Chains in LCC analysis by developing OS cost model for a hypothetical reusable space transportation vehicle (HSTV) and suggests further uses of the Markov Chain process as a design-aid tool.

Cheating at the end to avoid regret.

Science.gov (United States)

Effron, Daniel A; Bryan, Christopher J; Murnighan, J Keith

2015-09-01

How do people behave when they face a finite series of opportunities to cheat with little or no risk of detection? In 4 experiments and a small meta-analysis, we analyzed over 25,000 cheating opportunities faced by over 2,500 people. The results suggested that the odds of cheating are almost 3 times higher at the end of a series than earlier. Participants could cheat in 1 of 2 ways: They could lie about the outcome of a private coin flip to get a payoff that they would otherwise not receive (Studies 1-3) or they could overbill for their work (Study 4). We manipulated the number of cheating opportunities they expected but held the actual number of opportunities constant. The data showed that the likelihood of cheating and the extent of dishonesty were both greater when people believed that they were facing a last choice. Mediation analyses suggested that anticipatory regret about passing up a chance to enrich oneself drove this cheat-at-the-end effect. We found no support for alternative explanations based on the possibility that multiple cheating opportunities depleted people's self-control, eroded their moral standards, or made them feel that they had earned the right to cheat. The data also suggested that the cheat-at-the-end effect may be limited to relatively short series of cheating opportunities (i.e., n < 20). Our discussion addresses the psychological and behavioral dynamics of repeated ethical choices. (c) 2015 APA, all rights reserved).

Generalized Markov branching models

OpenAIRE

Li, Junping

2005-01-01

In this thesis, we first considered a modified Markov branching process incorporating both state-independent immigration and resurrection. After establishing the criteria for regularity and uniqueness, explicit expressions for the extinction probability and mean extinction time are presented. The criteria for recurrence and ergodicity are also established. In addition, an explicit expression for the equilibrium distribution is presented.\\ud \\ud We then moved on to investigate the basic proper...

Markov chain model for demersal fish catch analysis in Indonesia

Science.gov (United States)

Firdaniza; Gusriani, N.

2018-03-01

As an archipelagic country, Indonesia has considerable potential fishery resources. One of the fish resources that has high economic value is demersal fish. Demersal fish is a fish with a habitat in the muddy seabed. Demersal fish scattered throughout the Indonesian seas. Demersal fish production in each Indonesia’s Fisheries Management Area (FMA) varies each year. In this paper we have discussed the Markov chain model for demersal fish yield analysis throughout all Indonesia’s Fisheries Management Area. Data of demersal fish catch in every FMA in 2005-2014 was obtained from Directorate of Capture Fisheries. From this data a transition probability matrix is determined by the number of transitions from the catch that lie below the median or above the median. The Markov chain model of demersal fish catch data was an ergodic Markov chain model, so that the limiting probability of the Markov chain model can be determined. The predictive value of demersal fishing yields was obtained by calculating the combination of limiting probability with average catch results below the median and above the median. The results showed that for 2018 and long-term demersal fishing results in most of FMA were below the median value.

Adiabatic condition and the quantum hitting time of Markov chains

International Nuclear Information System (INIS)

Krovi, Hari; Ozols, Maris; Roland, Jeremie

2010-01-01

We present an adiabatic quantum algorithm for the abstract problem of searching marked vertices in a graph, or spatial search. Given a random walk (or Markov chain) P on a graph with a set of unknown marked vertices, one can define a related absorbing walk P ' where outgoing transitions from marked vertices are replaced by self-loops. We build a Hamiltonian H(s) from the interpolated Markov chain P(s)=(1-s)P+sP ' and use it in an adiabatic quantum algorithm to drive an initial superposition over all vertices to a superposition over marked vertices. The adiabatic condition implies that, for any reversible Markov chain and any set of marked vertices, the running time of the adiabatic algorithm is given by the square root of the classical hitting time. This algorithm therefore demonstrates a novel connection between the adiabatic condition and the classical notion of hitting time of a random walk. It also significantly extends the scope of previous quantum algorithms for this problem, which could only obtain a full quadratic speedup for state-transitive reversible Markov chains with a unique marked vertex.

A note on asymptotic expansions for Markov chains using operator theory

DEFF Research Database (Denmark)

Jensen, J.L.

1987-01-01

We consider asymptotic expansions for sums Sn on the form Sn = fhook0(X0) + fhook(X1, X0) + ... + fhook(Xn, Xn-1), where Xi is a Markov chain. Under different ergodicity conditions on the Markov chain and certain conditional moment conditions on fhook(Xi, Xi-1), a simple representation...

Identification of Optimal Policies in Markov Decision Processes

Czech Academy of Sciences Publication Activity Database

Sladký, Karel

46 2010, č. 3 (2010), s. 558-570 ISSN 0023-5954. [International Conference on Mathematical Methods in Economy and Industry. České Budějovice, 15.06.2009-18.06.2009] R&D Projects: GA ČR(CZ) GA402/08/0107; GA ČR GA402/07/1113 Institutional research plan: CEZ:AV0Z10750506 Keywords : finite state Markov decision processes * discounted and average costs * elimination of suboptimal policies Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.461, year: 2010 http://library.utia.cas.cz/separaty/2010/E/sladky-identification of optimal policies in markov decision processes.pdf

Examining Arizona's Policy Response Post "Flores v. Arizona" in Educating K-12 English Language Learners

Science.gov (United States)

Jimenez-Silva, Margarita; Gomez, Laura; Cisneros, Jesus

2014-01-01

This article provides an analysis of Arizona's policy response in educating English language learners by conducting a narrative review. A critical Latina/o theory approach was used to analyze the data. This study reveals 5 salient policy responses: (a) severely limit bilingual education, (b) develop controversial funding solutions, (c) implement a…

MARKOV GRAPHS OF ONE–DIMENSIONAL DYNAMICAL SYSTEMS AND THEIR DISCRETE ANALOGUES AND THEIR DISCRETE ANALOGUES

Directory of Open Access Journals (Sweden)

SERGIY KOZERENKO

2016-04-01

Full Text Available One feature of the famous Sharkovsky’s theorem is that it can be proved using digraphs of a special type (the so–called Markov graphs. The most general definition assigns a Markov graph to every continuous map from the topological graph to itself. We show that this definition is too broad, i.e. every finite digraph can be viewed as a Markov graph of some one–dimensional dynamical system on a tree. We therefore consider discrete analogues of Markov graphs for vertex maps on combinatorial trees and characterize all maps on trees whose discrete Markov graphs are of the following types: complete, complete bipartite, the disjoint union of cycles, with every arc being a loop.

Martingales and Markov chains solved exercises and elements of theory

CERN Document Server

Baldi, Paolo; Priouret, Pierre

2002-01-01

CONDITIONAL EXPECTATIONSIntroductionDefinition and First PropertiesConditional Expectations and Conditional LawsExercisesSolutionsSTOCHASTIC PROCESSESGeneral FactsStopping TimesExercisesSolutionsMARTINGALESFirst DefinitionsFirst PropertiesThe Stopping TheoremMaximal InequalitiesSquare Integral MartingalesConvergence TheoremsRegular MartingalesExercisesProblemsSolutionsMARKOV CHAINSTransition Matrices, Markov ChainsConstruction and ExistenceComputations on the Canonical ChainPotential OperatorsPassage ProblemsRecurrence, TransienceRecurrent Irreducible ChainsPeriodicityExercisesProblemsSolution

Fostering learners' interaction with content: A learner-centered mobile device interface

Science.gov (United States)

Abdous, M.

2015-12-01

With the ever-increasing omnipresence of mobile devices in student life, leveraging smart devices to foster students' interaction with course content is critical. Following a learner-centered design iterative approach, we designed a mobile interface that may enable learners to access and interact with online course content efficiently and intuitively. Our design process leveraged recent technologies, such as bootstrap, Google's Material Design, HTML5, and JavaScript to design an intuitive, efficient, and portable mobile interface with a variety of built-in features, including context sensitive bookmarking, searching, progress tracking, captioning, and transcript display. The mobile interface also offers students the ability to ask context-related questions and to complete self-checks as they watch audio/video presentations. Our design process involved ongoing iterative feedback from learners, allowing us to refine and tweak the interface to provide learners with a unified experience across platforms and devices. The innovative combination of technologies built around well-structured and well-designed content seems to provide an effective learning experience to mobile learners. Early feedback indicates a high level of satisfaction with the interface's efficiency, intuitiveness, and robustness from both students and faculty.

Math Autobiographies: A Window into Teachers' Identities as Mathematics Learners

Science.gov (United States)

McCulloch, Allison W.; Marshall, Patricia L.; DeCuir-Gunby, Jessica T.; Caldwell, Ticola S.

2013-01-01

Mathematics autobiographies have the potential to help teachers reflect on their identities as mathematics learners and to understand their role in the development of their students' mathematics identities. This paper reports on a professional development project for K-2 teachers (n = 41), in which participants were asked to write mathematics…

A reward semi-Markov process with memory for wind speed modeling

Science.gov (United States)

Petroni, F.; D'Amico, G.; Prattico, F.

2012-04-01

The increasing interest in renewable energy leads scientific research to find a better way to recover most of the available energy. Particularly, the maximum energy recoverable from wind is equal to 59.3% of that available (Betz law) at a specific pitch angle and when the ratio between the wind speed in output and in input is equal to 1/3. The pitch angle is the angle formed between the airfoil of the blade of the wind turbine and the wind direction. Old turbine and a lot of that actually marketed, in fact, have always the same invariant geometry of the airfoil. This causes that wind turbines will work with an efficiency that is lower than 59.3%. New generation wind turbines, instead, have a system to variate the pitch angle by rotating the blades. This system able the wind turbines to recover, at different wind speed, always the maximum energy, working in Betz limit at different speed ratios. A powerful system control of the pitch angle allows the wind turbine to recover better the energy in transient regime. A good stochastic model for wind speed is then needed to help both the optimization of turbine design and to assist the system control to predict the value of the wind speed to positioning the blades quickly and correctly. The possibility to have synthetic data of wind speed is a powerful instrument to assist designer to verify the structures of the wind turbines or to estimate the energy recoverable from a specific site. To generate synthetic data, Markov chains of first or higher order are often used [1,2,3]. In particular in [1] is presented a comparison between a first-order Markov chain and a second-order Markov chain. A similar work, but only for the first-order Markov chain, is conduced by [2], presenting the probability transition matrix and comparing the energy spectral density and autocorrelation of real and synthetic wind speed data. A tentative to modeling and to join speed and direction of wind is presented in [3], by using two models, first

Markov chain modelling of pitting corrosion in underground pipelines

Energy Technology Data Exchange (ETDEWEB)

Caleyo, F. [Departamento de Ingenieri' a Metalurgica, ESIQIE, IPN, UPALM Edif. 7, Zacatenco, Mexico D. F. 07738 (Mexico)], E-mail: fcaleyo@gmail.com; Velazquez, J.C. [Departamento de Ingenieri' a Metalurgica, ESIQIE, IPN, UPALM Edif. 7, Zacatenco, Mexico D. F. 07738 (Mexico); Valor, A. [Facultad de Fisica, Universidad de La Habana, San Lazaro y L, Vedado, 10400 La Habana (Cuba); Hallen, J.M. [Departamento de Ingenieri' a Metalurgica, ESIQIE, IPN, UPALM Edif. 7, Zacatenco, Mexico D. F. 07738 (Mexico)

2009-09-15

A continuous-time, non-homogenous linear growth (pure birth) Markov process has been used to model external pitting corrosion in underground pipelines. The closed form solution of Kolmogorov's forward equations for this type of Markov process is used to describe the transition probability function in a discrete pit depth space. The identification of the transition probability function can be achieved by correlating the stochastic pit depth mean with the deterministic mean obtained experimentally. Monte-Carlo simulations previously reported have been used to predict the time evolution of the mean value of the pit depth distribution for different soil textural classes. The simulated distributions have been used to create an empirical Markov chain-based stochastic model for predicting the evolution of pitting corrosion depth and rate distributions from the observed properties of the soil. The proposed model has also been applied to pitting corrosion data from pipeline repeated in-line inspections and laboratory immersion experiments.

Markov chain modelling of pitting corrosion in underground pipelines

International Nuclear Information System (INIS)

Caleyo, F.; Velazquez, J.C.; Valor, A.; Hallen, J.M.

2009-01-01

A continuous-time, non-homogenous linear growth (pure birth) Markov process has been used to model external pitting corrosion in underground pipelines. The closed form solution of Kolmogorov's forward equations for this type of Markov process is used to describe the transition probability function in a discrete pit depth space. The identification of the transition probability function can be achieved by correlating the stochastic pit depth mean with the deterministic mean obtained experimentally. Monte-Carlo simulations previously reported have been used to predict the time evolution of the mean value of the pit depth distribution for different soil textural classes. The simulated distributions have been used to create an empirical Markov chain-based stochastic model for predicting the evolution of pitting corrosion depth and rate distributions from the observed properties of the soil. The proposed model has also been applied to pitting corrosion data from pipeline repeated in-line inspections and laboratory immersion experiments.

Assessing Learner Satisfaction by Simultaneously Measuring Learner Attitude, Motivation, Loyalty and Service Quality in English Academies

Science.gov (United States)

Huong, Vu Thi; Casadesus, Marti; Marimon, Frederic

2017-01-01

The aims of this study are threefold in their approach to English academy teaching: (i) to assess learner satisfaction, (ii) to assess the impact of satisfaction on loyalty and (iii) to assess the three constructs that we considered to be the antecedents of learner satisfaction: learner motivation, learner attitude and service quality. To collect…

An interlacing theorem for reversible Markov chains

International Nuclear Information System (INIS)

Grone, Robert; Salamon, Peter; Hoffmann, Karl Heinz

2008-01-01

Reversible Markov chains are an indispensable tool in the modeling of a vast class of physical, chemical, biological and statistical problems. Examples include the master equation descriptions of relaxing physical systems, stochastic optimization algorithms such as simulated annealing, chemical dynamics of protein folding and Markov chain Monte Carlo statistical estimation. Very often the large size of the state spaces requires the coarse graining or lumping of microstates into fewer mesoscopic states, and a question of utmost importance for the validity of the physical model is how the eigenvalues of the corresponding stochastic matrix change under this operation. In this paper we prove an interlacing theorem which gives explicit bounds on the eigenvalues of the lumped stochastic matrix. (fast track communication)

An interlacing theorem for reversible Markov chains

Energy Technology Data Exchange (ETDEWEB)

Grone, Robert; Salamon, Peter [Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182-7720 (United States); Hoffmann, Karl Heinz [Institut fuer Physik, Technische Universitaet Chemnitz, D-09107 Chemnitz (Germany)

2008-05-30

Reversible Markov chains are an indispensable tool in the modeling of a vast class of physical, chemical, biological and statistical problems. Examples include the master equation descriptions of relaxing physical systems, stochastic optimization algorithms such as simulated annealing, chemical dynamics of protein folding and Markov chain Monte Carlo statistical estimation. Very often the large size of the state spaces requires the coarse graining or lumping of microstates into fewer mesoscopic states, and a question of utmost importance for the validity of the physical model is how the eigenvalues of the corresponding stochastic matrix change under this operation. In this paper we prove an interlacing theorem which gives explicit bounds on the eigenvalues of the lumped stochastic matrix. (fast track communication)

Pairwise Choice Markov Chains

OpenAIRE

Ragain, Stephen; Ugander, Johan

2016-01-01

As datasets capturing human choices grow in richness and scale---particularly in online domains---there is an increasing need for choice models that escape traditional choice-theoretic axioms such as regularity, stochastic transitivity, and Luce's choice axiom. In this work we introduce the Pairwise Choice Markov Chain (PCMC) model of discrete choice, an inferentially tractable model that does not assume any of the above axioms while still satisfying the foundational axiom of uniform expansio...

Distinguishing Hidden Markov Chains

OpenAIRE

Kiefer, Stefan; Sistla, A. Prasad

2015-01-01

Hidden Markov Chains (HMCs) are commonly used mathematical models of probabilistic systems. They are employed in various fields such as speech recognition, signal processing, and biological sequence analysis. We consider the problem of distinguishing two given HMCs based on an observation sequence that one of the HMCs generates. More precisely, given two HMCs and an observation sequence, a distinguishing algorithm is expected to identify the HMC that generates the observation sequence. Two HM...

Pemodelan Markov Switching Autoregressive

OpenAIRE

Ariyani, Fiqria Devi; Warsito, Budi; Yasin, Hasbi

2014-01-01

Transition from depreciation to appreciation of exchange rate is one of regime switching that ignored by classic time series model, such as ARIMA, ARCH, or GARCH. Therefore, economic variables are modeled by Markov Switching Autoregressive (MSAR) which consider the regime switching. MLE is not applicable to parameters estimation because regime is an unobservable variable. So that filtering and smoothing process are applied to see the regime probabilities of observation. Using this model, tran...

Multi-dimensional quasitoeplitz Markov chains

Directory of Open Access Journals (Sweden)

Alexander N. Dudin

1999-01-01

Full Text Available This paper deals with multi-dimensional quasitoeplitz Markov chains. We establish a sufficient equilibrium condition and derive a functional matrix equation for the corresponding vector-generating function, whose solution is given algorithmically. The results are demonstrated in the form of examples and applications in queues with BMAP-input, which operate in synchronous random environment.

Finding exact constants in a Markov model of Zipfs law generation

Science.gov (United States)

Bochkarev, V. V.; Lerner, E. Yu.; Nikiforov, A. A.; Pismenskiy, A. A.

2017-12-01

According to the classical Zipfs law, the word frequency is a power function of the word rank with an exponent -1. The objective of this work is to find multiplicative constant in a Markov model of word generation. Previously, the case of independent letters was mathematically strictly investigated in [Bochkarev V V and Lerner E Yu 2017 International Journal of Mathematics and Mathematical Sciences Article ID 914374]. Unfortunately, the methods used in this paper cannot be generalized in case of Markov chains. The search of the correct formulation of the Markov generalization of this results was performed using experiments with different ergodic matrices of transition probability P. Combinatory technique allowed taking into account all the words with probability of more than e -300 in case of 2 by 2 matrices. It was experimentally proved that the required constant in the limit is equal to the value reciprocal to conditional entropy of matrix row P with weights presenting the elements of the vector π of the stationary distribution of the Markov chain.

Adaptations for English Language Learners: Differentiating between Linguistic and Instructional Accommodations

Science.gov (United States)

Pappamihiel, N. Eleni; Lynn, C. Allen

2016-01-01

While many teachers and teacher educators in the United States K-12 system acknowledge that the English language learners (ELLs) in our schools need modifications and accommodations to help them succeed in school, few attempt to parse out how different types of accommodations may affect learning in the mainstream classroom, specifically linguistic…

Robust filtering and prediction for systems with embedded finite-state Markov-Chain dynamics

International Nuclear Information System (INIS)

Pate, E.B.

1986-01-01

This research developed new methodologies for the design of robust near-optimal filters/predictors for a class of system models that exhibit embedded finite-state Markov-chain dynamics. These methodologies are developed through the concepts and methods of stochastic model building (including time-series analysis), game theory, decision theory, and filtering/prediction for linear dynamic systems. The methodology is based on the relationship between the robustness of a class of time-series models and quantization which is applied to the time series as part of the model identification process. This relationship is exploited by utilizing the concept of an equivalence, through invariance of spectra, between the class of Markov-chain models and the class of autoregressive moving average (ARMA) models. This spectral equivalence permits a straightforward implementation of the desirable robust properties of the Markov-chain approximation in a class of models which may be applied in linear-recursive form in a linear Kalman filter/predictor structure. The linear filter/predictor structure is shown to provide asymptotically optimal estimates of states which represent one or more integrations of the Markov-chain state. The development of a new saddle-point theorem for a game based on the Markov-chain model structure gives rise to a technique for determining a worst case Markov-chain process, upon which a robust filter/predictor design if based

Markov Trends in Macroeconomic Time Series

NARCIS (Netherlands)

R. Paap (Richard)

1997-01-01

textabstractMany macroeconomic time series are characterised by long periods of positive growth, expansion periods, and short periods of negative growth, recessions. A popular model to describe this phenomenon is the Markov trend, which is a stochastic segmented trend where the slope depends on the

Model Checking Structured Infinite Markov Chains

NARCIS (Netherlands)

Remke, Anne Katharina Ingrid

2008-01-01

In the past probabilistic model checking hast mostly been restricted to finite state models. This thesis explores the possibilities of model checking with continuous stochastic logic (CSL) on infinite-state Markov chains. We present an in-depth treatment of model checking algorithms for two special

The Consensus String Problem and the Complexity of Comparing Hidden Markov Models

DEFF Research Database (Denmark)

Lyngsø, Rune Bang; Pedersen, Christian Nørgaard Storm

2002-01-01

The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960s, and has since then been applied to numerous problems, e.g. biological sequence analysis. Most applications of hidden Markov models are based on efficient algorithms for computing......-norms. We discuss the applicability of the technique used for proving the hardness of comparing two hidden Markov models under the L1-norm to other measures of distance between probability distributions. In particular, we show that it cannot be used for proving NP-hardness of determining the Kullback...

When learners become teachers: a review of peer teaching in medical student education.

Science.gov (United States)

Benè, Kristen L; Bergus, George

2014-01-01

Peer teaching engages students as teachers and is widely used in K-12 education, many universities, and increasingly in medical schools. It draws on the social and cognitive congruence between learner and teacher and can be attractive to medical schools faced with a growing number of learners but a static faculty size. Peer teachers can give lectures on assigned topics, lead problem-based learning sessions, and provide one on one support to classmates in the form of tutoring. We undertook a narrative review of research on peer teachers in medical school, specifically investigating how medical students are impacted by being peer teachers and how having a peer teacher impacts learners. Studies have shown that peer teaching has a primarily positive impact on both the peer teacher and the learners. In the setting of problem-based learning courses or clinical skills instruction, medical students' performance on tests of knowledge or skills is similar whether they have faculty instructors or peer teachers. There is also strong evidence that being a peer teacher enhances the learning of the peer teacher relative to the content being taught. It is common for peer teachers to lack confidence in their abilities to successfully teach, and they appreciate receiving training related to their teaching role. We find evidence from several different educational settings that peer teaching benefits both the peer teachers and the learners. This suggests that peer teaching is a valuable methodology for medical schools to engage learners as teachers.

Error Bounds for Augmented Truncations of Discrete-Time Block-Monotone Markov Chains under Geometric Drift Conditions

OpenAIRE

Masuyama, Hiroyuki

2014-01-01

In this paper we study the augmented truncation of discrete-time block-monotone Markov chains under geometric drift conditions. We first present a bound for the total variation distance between the stationary distributions of an original Markov chain and its augmented truncation. We also obtain such error bounds for more general cases, where an original Markov chain itself is not necessarily block monotone but is blockwise dominated by a block-monotone Markov chain. Finally,...

Inference with constrained hidden Markov models in PRISM

DEFF Research Database (Denmark)

Christiansen, Henning; Have, Christian Theil; Lassen, Ole Torp

2010-01-01

A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference. De......_different are integrated. We experimentally validate our approach on the biologically motivated problem of global pairwise alignment.......A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference...

An Application of Graph Theory in Markov Chains Reliability Analysis

Directory of Open Access Journals (Sweden)

Pavel Skalny

2014-01-01

Full Text Available The paper presents reliability analysis which was realized for an industrial company. The aim of the paper is to present the usage of discrete time Markov chains and the flow in network approach. Discrete Markov chains a well-known method of stochastic modelling describes the issue. The method is suitable for many systems occurring in practice where we can easily distinguish various amount of states. Markov chains are used to describe transitions between the states of the process. The industrial process is described as a graph network. The maximal flow in the network corresponds to the production. The Ford-Fulkerson algorithm is used to quantify the production for each state. The combination of both methods are utilized to quantify the expected value of the amount of manufactured products for the given time period.

Mission reliability of semi-Markov systems under generalized operational time requirements

International Nuclear Information System (INIS)

Wu, Xiaoyue; Hillston, Jane

2015-01-01

Mission reliability of a system depends on specific criteria for mission success. To evaluate the mission reliability of some mission systems that do not need to work normally for the whole mission time, two types of mission reliability for such systems are studied. The first type corresponds to the mission requirement that the system must remain operational continuously for a minimum time within the given mission time interval, while the second corresponds to the mission requirement that the total operational time of the system within the mission time window must be greater than a given value. Based on Markov renewal properties, matrix integral equations are derived for semi-Markov systems. Numerical algorithms and a simulation procedure are provided for both types of mission reliability. Two examples are used for illustration purposes. One is a one-unit repairable Markov system, and the other is a cold standby semi-Markov system consisting of two components. By the proposed approaches, the mission reliability of systems with time redundancy can be more precisely estimated to avoid possible unnecessary redundancy of system resources. - Highlights: • Two types of mission reliability under generalized requirements are defined. • Equations for both types of reliability are derived for semi-Markov systems. • Numerical methods are given for solving both types of reliability. • Simulation procedure is given for estimating both types of reliability. • Verification of the numerical methods is given by the results of simulation

Markov Chain Models for the Stochastic Modeling of Pitting Corrosion

OpenAIRE

Valor, A.; Caleyo, F.; Alfonso, L.; Velázquez, J. C.; Hallen, J. M.

2013-01-01

The stochastic nature of pitting corrosion of metallic structures has been widely recognized. It is assumed that this kind of deterioration retains no memory of the past, so only the current state of the damage influences its future development. This characteristic allows pitting corrosion to be categorized as a Markov process. In this paper, two different models of pitting corrosion, developed using Markov chains, are presented. Firstly, a continuous-time, nonhomogeneous linear growth (pure ...

Musical Markov Chains

Science.gov (United States)

Volchenkov, Dima; Dawin, Jean René

A system for using dice to compose music randomly is known as the musical dice game. The discrete time MIDI models of 804 pieces of classical music written by 29 composers have been encoded into the transition matrices and studied by Markov chains. Contrary to human languages, entropy dominates over redundancy, in the musical dice games based on the compositions of classical music. The maximum complexity is achieved on the blocks consisting of just a few notes (8 notes, for the musical dice games generated over Bach's compositions). First passage times to notes can be used to resolve tonality and feature a composer.

Markov chain analysis of single spin flip Ising simulations

International Nuclear Information System (INIS)

Hennecke, M.

1997-01-01

The Markov processes defined by random and loop-based schemes for single spin flip attempts in Monte Carlo simulations of the 2D Ising model are investigated, by explicitly constructing their transition matrices. Their analysis reveals that loops over all lattice sites using a Metropolis-type single spin flip probability often do not define ergodic Markov chains, and have distorted dynamical properties even if they are ergodic. The transition matrices also enable a comparison of the dynamics of random versus loop spin selection and Glauber versus Metropolis probabilities

ANALYSING ACCEPTANCE SAMPLING PLANS BY MARKOV CHAINS

Directory of Open Access Journals (Sweden)

Mohammad Mirabi

2012-01-01

Full Text Available

ENGLISH ABSTRACT: In this research, a Markov analysis of acceptance sampling plans in a single stage and in two stages is proposed, based on the quality of the items inspected. In a stage of this policy, if the number of defective items in a sample of inspected items is more than the upper threshold, the batch is rejected. However, the batch is accepted if the number of defective items is less than the lower threshold. Nonetheless, when the number of defective items falls between the upper and lower thresholds, the decision-making process continues to inspect the items and collect further samples. The primary objective is to determine the optimal values of the upper and lower thresholds using a Markov process to minimise the total cost associated with a batch acceptance policy. A solution method is presented, along with a numerical demonstration of the application of the proposed methodology.

AFRIKAANSE OPSOMMING: In hierdie navorsing word ’n Markov-ontleding gedoen van aannamemonsternemingsplanne wat plaasvind in ’n enkele stap of in twee stappe na gelang van die kwaliteit van die items wat geïnspekteer word. Indien die eerste monster toon dat die aantal defektiewe items ’n boonste grens oorskry, word die lot afgekeur. Indien die eerste monster toon dat die aantal defektiewe items minder is as ’n onderste grens, word die lot aanvaar. Indien die eerste monster toon dat die aantal defektiewe items in die gebied tussen die boonste en onderste grense lê, word die besluitnemingsproses voortgesit en verdere monsters word geneem. Die primêre doel is om die optimale waardes van die booonste en onderste grense te bepaal deur gebruik te maak van ’n Markov-proses sodat die totale koste verbonde aan die proses geminimiseer kan word. ’n Oplossing word daarna voorgehou tesame met ’n numeriese voorbeeld van die toepassing van die voorgestelde oplossing.

Computing characterizations of drugs for ion channels and receptors using Markov models

CERN Document Server

Tveito, Aslak

2016-01-01

Flow of ions through voltage gated channels can be represented theoretically using stochastic differential equations where the gating mechanism is represented by a Markov model. The flow through a channel can be manipulated using various drugs, and the effect of a given drug can be reflected by changing the Markov model. These lecture notes provide an accessible introduction to the mathematical methods needed to deal with these models. They emphasize the use of numerical methods and provide sufficient details for the reader to implement the models and thereby study the effect of various drugs. Examples in the text include stochastic calcium release from internal storage systems in cells, as well as stochastic models of the transmembrane potential. Well known Markov models are studied and a systematic approach to including the effect of mutations is presented. Lastly, the book shows how to derive the optimal properties of a theoretical model of a drug for a given mutation defined in terms of a Markov model.

Hidden Markov Models for Human Genes

DEFF Research Database (Denmark)

Baldi, Pierre; Brunak, Søren; Chauvin, Yves

1997-01-01

We analyse the sequential structure of human genomic DNA by hidden Markov models. We apply models of widely different design: conventional left-right constructs and models with a built-in periodic architecture. The models are trained on segments of DNA sequences extracted such that they cover com...

Model Checking Infinite-State Markov Chains

NARCIS (Netherlands)

Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.; Cloth, L.

2004-01-01

In this paper algorithms for model checking CSL (continuous stochastic logic) against infinite-state continuous-time Markov chains of so-called quasi birth-death type are developed. In doing so we extend the applicability of CSL model checking beyond the recently proposed case for finite-state

Nuclear security assessment with Markov model approach

International Nuclear Information System (INIS)

Suzuki, Mitsutoshi; Terao, Norichika

2013-01-01

Nuclear security risk assessment with the Markov model based on random event is performed to explore evaluation methodology for physical protection in nuclear facilities. Because the security incidences are initiated by malicious and intentional acts, expert judgment and Bayes updating are used to estimate scenario and initiation likelihood, and it is assumed that the Markov model derived from stochastic process can be applied to incidence sequence. Both an unauthorized intrusion as Design Based Threat (DBT) and a stand-off attack as beyond-DBT are assumed to hypothetical facilities, and performance of physical protection and mitigation and minimization of consequence are investigated to develop the assessment methodology in a semi-quantitative manner. It is shown that cooperation between facility operator and security authority is important to respond to the beyond-DBT incidence. (author)

Lithofacies cyclicity determination in the guaduas formation (Colombia using Markov chains

Directory of Open Access Journals (Sweden)

Jorge Eliecer Mariño Martinez

2016-07-01

Full Text Available Statistical embedded Markov Chain processes were used to analyze facies transitions and to determine the stacking pattern of the lithofacies of the Guaduas Formation. Twelve Lithofacies were found and characterized based on lithology and sedimentary structures in four stratigraphic sections. The findings were compared with a previous assemblage of lithofacies, interpretations of sedimentary environments, and depositional systems.  As a result, four depositional Systems were established. Through the statistical analyses of facies transitions it was found that tidal facies are prevalent in the Socota section, especially in the upper part, whereas in the Sogamoso, Umbita and Peñas de Sutatausa sections, fluvial facies are prevalent in the upper part of the sections, and follow a regressive sequence with more continental deposits around the upper part of the sections. For each of these sections the Markov Chain transition matrices illustrates a strong interaction between tidal facies and fluvial facies, specially in the Peñas de Sutatausa matrix, where facies 6, made up of tidal deposits, appears several times. From the facies model and Markov Chain analyses, it is evident that the Guaduas Formation is a cyclic sequence in which the Markov facies repetitions are consistent with the lithofacies analyses conducted in previous stratigraphic studies. The results reveal that the Markov Chain statistical process can be used to predict stratigraphy in order to correlate contiguous geologically unexplored areas in the Guaduas Formation, where much work relating to correlation and the continuity of coal beds has yet to be done.    Determinacion de la ciclicidad de las facies en la formacion Guaduas (Colombia usando las cadenas de Markov Resumen Se utilizaron los procesos estadísticos de las cadenas de Markov para analizar las transiciones de facies y para determinar el patrón de apilamiento de las litofacies de la formación Guaduas. Se encontraron y

An algorithmic approach for the dynamic reliability analysis of non-repairable multi-state weighted k-out-of-n:G system

International Nuclear Information System (INIS)

Eryilmaz, Serkan; Rıza Bozbulut, Ali

2014-01-01

In this paper, we study a multi-state weighted k-out-of-n:G system model in a dynamic setup. In particular, we study the random time spent by the system with a minimum performance level of k. Our method is based on ordering the lifetimes of the system's components in different state subsets. Using this ordering along with the Monte-Carlo simulation algorithm, we obtain estimates of the mean and survival function of the time spent by the system in state k or above. We present illustrative computational results when the degradation in the components follows a Markov process. - Highlights: • A multi-state weighted k-out-of-n:G system is studied. • A Monte-Carlo simulation algorithm is provided for the dynamic analysis. • Numerics are presented when the components' degradation follow the Markov process

Markov Random Fields on Triangle Meshes

DEFF Research Database (Denmark)

Andersen, Vedrana; Aanæs, Henrik; Bærentzen, Jakob Andreas

2010-01-01

In this paper we propose a novel anisotropic smoothing scheme based on Markov Random Fields (MRF). Our scheme is formulated as two coupled processes. A vertex process is used to smooth the mesh by displacing the vertices according to a MRF smoothness prior, while an independent edge process label...

Bayesian analysis for reversible Markov chains

NARCIS (Netherlands)

Diaconis, P.; Rolles, S.W.W.

2006-01-01

We introduce a natural conjugate prior for the transition matrix of a reversible Markov chain. This allows estimation and testing. The prior arises from random walk with reinforcement in the same way the Dirichlet prior arises from Pólya’s urn. We give closed form normalizing constants, a simple

Hidden Markov models for labeled sequences

DEFF Research Database (Denmark)

Krogh, Anders Stærmose

1994-01-01

A hidden Markov model for labeled observations, called a class HMM, is introduced and a maximum likelihood method is developed for estimating the parameters of the model. Instead of training it to model the statistics of the training sequences it is trained to optimize recognition. It resembles MMI...

Limits of performance for the model reduction problem of hidden Markov models

KAUST Repository

Kotsalis, Georgios

2015-12-15

We introduce system theoretic notions of a Hankel operator, and Hankel norm for hidden Markov models. We show how the related Hankel singular values provide lower bounds on the norm of the difference between a hidden Markov model of order n and any lower order approximant of order n̂ < n.

Limits of performance for the model reduction problem of hidden Markov models

KAUST Repository

Kotsalis, Georgios; Shamma, Jeff S.

2015-01-01

We introduce system theoretic notions of a Hankel operator, and Hankel norm for hidden Markov models. We show how the related Hankel singular values provide lower bounds on the norm of the difference between a hidden Markov model of order n and any lower order approximant of order n̂ < n.

The Relationship between Learner Autonomy and Vocabulary Learning Strategies in Iranian EFL Learners with Different Language Proficiency Level

Directory of Open Access Journals (Sweden)

Ebrahim Azimi Mohammad Abadi

2013-05-01

Full Text Available Vocabulary learning is incredibly noteworthy to English language acquisition. It is unfeasible for a learner to communicate without the required vocabulary. In high education levels, learners are habitually forced to become autonomous and make conscious effort to learn vocabulary outside of the classroom. Consequently, the autonomy of the learners plays an important role in developing and enhancing their vocabulary. Learner autonomy is a huge assistance for learners in vocabulary learning since it provides the learners with numerous diverse privileges such as independency from teacher. The researcher investigated whether there is any statistically significant relationship between learner autonomy and vocabulary learning strategies use in Iranian EFL learners with different language proficiency levels. To meet the above purpose, a total number of 190 male and female EFL learners participated in this study. The methodology underlying this study was quantitative (thorough the administration of two questionnaires and two language proficiency test – TOEFL for advanced group, and Nelson for intermediate level. The quantitative data was analyzed using a set of correlational analysis revealing a significant positive correlation between learner autonomy and vocabulary learning strategies use in high proficient group, and a significant positive relationship between these two constructs in low proficient group, however not as strong as in the advanced group.

Toward Adversarial Online Learning and the Science of Deceptive Machines

Science.gov (United States)

2015-11-14

games (Blum and Monsour 2007). We will define a notion of regret for secure online learning with respect to a static learner. The value of an action a......anomaly detection methods. The avail- ability of large amount of data requires the processing of data in a “streaming” fashion with online algorithms. Yet

Risk, rationality, and regret: responding to the uncertainty of childhood food anaphylaxis.

Science.gov (United States)

Hu, W; Kerridge, I; Kemp, A

2005-06-01

Risk and uncertainty are unavoidable in clinical medicine. In the case of childhood food allergy, the dysphoric experience of uncertainty is heightened by the perception of unpredictable danger to young children. Medicine has tended to respond to uncertainty with forms of rational decision making. Rationality cannot, however, resolve uncertainty and provides an insufficient account of risk. This paper compares the medical and parental accounts of two peanut allergic toddlers to highlight the value of emotions in decision making. One emotion in particular, regret, assists in explaining the actions taken to prevent allergic reactions, given the diffuse nature of responsibility for children. In this light, the assumption that doctors make rational judgments while patients have emotion led preferences is a false dichotomy. Reconciling medical and lay accounts requires acknowledgement of the interrelationship between the rational and the emotional, and may lead to more appropriate clinical decision making under conditions of uncertainty.

A Method for Driving Route Predictions Based on Hidden Markov Model

Directory of Open Access Journals (Sweden)

Ning Ye

2015-01-01

Full Text Available We present a driving route prediction method that is based on Hidden Markov Model (HMM. This method can accurately predict a vehicle’s entire route as early in a trip’s lifetime as possible without inputting origins and destinations beforehand. Firstly, we propose the route recommendation system architecture, where route predictions play important role in the system. Secondly, we define a road network model, normalize each of driving routes in the rectangular coordinate system, and build the HMM to make preparation for route predictions using a method of training set extension based on K-means++ and the add-one (Laplace smoothing technique. Thirdly, we present the route prediction algorithm. Finally, the experimental results of the effectiveness of the route predictions that is based on HMM are shown.

Harmonic spectral components in time sequences of Markov correlated events

Science.gov (United States)

Mazzetti, Piero; Carbone, Anna

2017-07-01

The paper concerns the analysis of the conditions allowing time sequences of Markov correlated events give rise to a line power spectrum having a relevant physical interest. It is found that by specializing the Markov matrix in order to represent closed loop sequences of events with arbitrary distribution, generated in a steady physical condition, a large set of line spectra, covering all possible frequency values, is obtained. The amplitude of the spectral lines is given by a matrix equation based on a generalized Markov matrix involving the Fourier transform of the distribution functions representing the time intervals between successive events of the sequence. The paper is a complement of a previous work where a general expression for the continuous power spectrum was given. In that case the Markov matrix was left in a more general form, thus preventing the possibility of finding line spectra of physical interest. The present extension is also suggested by the interest of explaining the emergence of a broad set of waves found in the electro and magneto-encephalograms, whose frequency ranges from 0.5 to about 40Hz, in terms of the effects produced by chains of firing neurons within the complex neural network of the brain. An original model based on synchronized closed loop sequences of firing neurons is proposed, and a few numerical simulations are reported as an application of the above cited equation.

Examining the Relationship between Emergent Literacy Skills and Invented Spelling in Prekindergarten Spanish-Speaking Dual Language Learners

Science.gov (United States)

Pendergast, Meghan; Bingham, Gary; Patton-Terry, Nicole

2015-01-01

The purpose of the present study was to examine associations among English and Spanish emergent literacy skills of prekindergarten (pre-K) Spanish-speaking dual language learners in relation to their English invented spelling. Study participants included 141 Spanish-speaking 4-year-old children enrolled in state-funded pre-K programs in a large…

Weighted-indexed semi-Markov models for modeling financial returns

International Nuclear Information System (INIS)

D’Amico, Guglielmo; Petroni, Filippo

2012-01-01

In this paper we propose a new stochastic model based on a generalization of semi-Markov chains for studying the high frequency price dynamics of traded stocks. We assume that the financial returns are described by a weighted-indexed semi-Markov chain model. We show, through Monte Carlo simulations, that the model is able to reproduce important stylized facts of financial time series such as the first-passage-time distributions and the persistence of volatility. The model is applied to data from the Italian and German stock markets from 1 January 2007 until the end of December 2010. (paper)

Data-driven Markov models and their application in the evaluation of adverse events in radiotherapy

CERN Document Server

Abler, Daniel; Davies, Jim; Dosanjh, Manjit; Jena, Raj; Kirkby, Norman; Peach, Ken

2013-01-01

Decision-making processes in medicine rely increasingly on modelling and simulation techniques; they are especially useful when combining evidence from multiple sources. Markov models are frequently used to synthesize the available evidence for such simulation studies, by describing disease and treatment progress, as well as associated factors such as the treatment's effects on a patient's life and the costs to society. When the same decision problem is investigated by multiple stakeholders, differing modelling assumptions are often applied, making synthesis and interpretation of the results difficult. This paper proposes a standardized approach towards the creation of Markov models. It introduces the notion of ‘general Markov models’, providing a common definition of the Markov models that underlie many similar decision problems, and develops a language for their specification. We demonstrate the application of this language by developing a general Markov model for adverse event analysis in radiotherapy ...

Developing the master learner: applying learning theory to the learner, the teacher, and the learning environment.

Science.gov (United States)

Schumacher, Daniel J; Englander, Robert; Carraccio, Carol

2013-11-01

As a result of the paradigm shift to a competency-based framework, both self-directed lifelong learning and learner-centeredness have become essential tenets of medical education. In the competency-based framework, learners drive their own educational process, and both learners and teachers share the responsibility for the path and content of learning. This learner-centered emphasis requires each physician to develop and maintain lifelong learning skills, which the authors propose culminate in becoming a "master leaner." To better understand the development of these skills and the attainment of that goal, the authors explore how learning theories inform the development of master learners and how to translate these theories into practical strategies for the learner, the teacher, and the learning environment so as to optimize this development.The authors begin by exploring self-determination theory, which lays the groundwork for understanding the motivation to learn. They next consider the theories of cognitive load and situated cognition, which inform the optimal context and environment for learning. Building from this foundation, the authors consider key educational theories that affect learners' abilities to serve as primary drivers of their learning, including self-directed learning (SDL); the self-assessment skills necessary for SDL; factors affecting self-assessment (self-concept, self-efficacy, illusory superiority, gap filling); and ways to mitigate the inaccuracies of self-assessment (reflection, self-monitoring, external information seeking, and self-directed assessment seeking).For each theory, they suggest practical action steps for the learner, the teacher, and the learning environment in an effort to provide a road map for developing master learners.

Learner-Generated Noticing Behavior by Novice Learners: Tracing the Effects of Learners' L1 on Their Emerging L2

Science.gov (United States)

Park, Eun Sung

2013-01-01

This study examines novice learners' self-generated input noticing approaches and strategies. It is motivated by previous research on input enhancement which yielded insights that learners are naturally prone to notice certain aspects of L2 input on their own without any external means to channel their attention. Two L1 groups (Japanese and…

Revisiting Temporal Markov Chains for Continuum modeling of Transport in Porous Media

Science.gov (United States)

Delgoshaie, A. H.; Jenny, P.; Tchelepi, H.

2017-12-01

The transport of fluids in porous media is dominated by flow­-field heterogeneity resulting from the underlying permeability field. Due to the high uncertainty in the permeability field, many realizations of the reference geological model are used to describe the statistics of the transport phenomena in a Monte Carlo (MC) framework. There has been strong interest in working with stochastic formulations of the transport that are different from the standard MC approach. Several stochastic models based on a velocity process for tracer particle trajectories have been proposed. Previous studies have shown that for high variances of the log-conductivity, the stochastic models need to account for correlations between consecutive velocity transitions to predict dispersion accurately. The correlated velocity models proposed in the literature can be divided into two general classes of temporal and spatial Markov models. Temporal Markov models have been applied successfully to tracer transport in both the longitudinal and transverse directions. These temporal models are Stochastic Differential Equations (SDEs) with very specific drift and diffusion terms tailored for a specific permeability correlation structure. The drift and diffusion functions devised for a certain setup would not necessarily be suitable for a different scenario, (e.g., a different permeability correlation structure). The spatial Markov models are simple discrete Markov chains that do not require case specific assumptions. However, transverse spreading of contaminant plumes has not been successfully modeled with the available correlated spatial models. Here, we propose a temporal discrete Markov chain to model both the longitudinal and transverse dispersion in a two-dimensional domain. We demonstrate that these temporal Markov models are valid for different correlation structures without modification. Similar to the temporal SDEs, the proposed model respects the limited asymptotic transverse spreading of

Learners' perceptions of learners regarded as having a homosexual orientation in an independent secondary school environment.

Science.gov (United States)

Mostert, Hendrik P; Myburgh, Chris; Poggenpoel, Marie

2012-10-04

In schools today discrimination based on sexual orientation takes place on a regular basis. This form of discrimination leads to aggression towards learners perceived to be homosexual, as well as towards those with a homosexual orientation. For more than 15 years South Africa has been a democratic country with laws that protect learners who have a homosexual orientation. Nevertheless, aggression and discrimination towards these learners still occur in schools. Aggression often leads to verbal and physical bullying of the victims by perpetrators. The objectives of this research were to explore and describe Grade 11 learners' experiences of aggression towards learners perceived to be homosexual as well as those with a homosexual orientation in an independent secondary school environment. The research design was qualitative, exploratory, descriptive and contextual in nature. The data for this investigation consisted of essays based on a published newspaper photograph, phenomenological group interviews, observations and field notes. Tesch's method of data analysis was used, and an independent coder assisted. Three themes were identified, discussed and supported by a literature control: that learners experience that it is right and acceptable to have a homosexual orientation; that they experience ambivalence towards homosexual orientation of learners; and experienced feelings that it is wrong to have a homosexual orientation. Recommended guidelines are provided to address aggression towards learners perceived to be homosexual and those with a homosexual orientation.

Fast-slow asymptotics for a Markov chain model of fast sodium current

Science.gov (United States)

Starý, Tomáš; Biktashev, Vadim N.

2017-09-01

We explore the feasibility of using fast-slow asymptotics to eliminate the computational stiffness of discrete-state, continuous-time deterministic Markov chain models of ionic channels underlying cardiac excitability. We focus on a Markov chain model of fast sodium current, and investigate its asymptotic behaviour with respect to small parameters identified in different ways.

Robust Dynamics and Control of a Partially Observed Markov Chain

International Nuclear Information System (INIS)

Elliott, R. J.; Malcolm, W. P.; Moore, J. P.

2007-01-01

In a seminal paper, Martin Clark (Communications Systems and Random Process Theory, Darlington, 1977, pp. 721-734, 1978) showed how the filtered dynamics giving the optimal estimate of a Markov chain observed in Gaussian noise can be expressed using an ordinary differential equation. These results offer substantial benefits in filtering and in control, often simplifying the analysis and an in some settings providing numerical benefits, see, for example Malcolm et al. (J. Appl. Math. Stoch. Anal., 2007, to appear).Clark's method uses a gauge transformation and, in effect, solves the Wonham-Zakai equation using variation of constants. In this article, we consider the optimal control of a partially observed Markov chain. This problem is discussed in Elliott et al. (Hidden Markov Models Estimation and Control, Applications of Mathematics Series, vol. 29, 1995). The innovation in our results is that the robust dynamics of Clark are used to compute forward in time dynamics for a simplified adjoint process. A stochastic minimum principle is established

Decomposition of conditional probability for high-order symbolic Markov chains

Science.gov (United States)

Melnik, S. S.; Usatenko, O. V.

2017-07-01

The main goal of this paper is to develop an estimate for the conditional probability function of random stationary ergodic symbolic sequences with elements belonging to a finite alphabet. We elaborate on a decomposition procedure for the conditional probability function of sequences considered to be high-order Markov chains. We represent the conditional probability function as the sum of multilinear memory function monomials of different orders (from zero up to the chain order). This allows us to introduce a family of Markov chain models and to construct artificial sequences via a method of successive iterations, taking into account at each step increasingly high correlations among random elements. At weak correlations, the memory functions are uniquely expressed in terms of the high-order symbolic correlation functions. The proposed method fills the gap between two approaches, namely the likelihood estimation and the additive Markov chains. The obtained results may have applications for sequential approximation of artificial neural network training.

A New Approach of an Intelligent E-Learning System Based on Learners' Skill Level and Learners' Success Rate

Science.gov (United States)

Mohamed, Hafidi; Lamia, Mahnane

2015-01-01

Learners usually meet cognitive overload and disorientation problems when using e-learning system. At present, most of the studies in e-learning either concentrate on the technological aspect or focus on adapting learner's interests or browsing behaviors, while, learner's skill level and learners' success rate is usually neglected. In this paper,…

Simulation based sequential Monte Carlo methods for discretely observed Markov processes

OpenAIRE

Neal, Peter

2014-01-01

Parameter estimation for discretely observed Markov processes is a challenging problem. However, simulation of Markov processes is straightforward using the Gillespie algorithm. We exploit this ease of simulation to develop an effective sequential Monte Carlo (SMC) algorithm for obtaining samples from the posterior distribution of the parameters. In particular, we introduce two key innovations, coupled simulations, which allow us to study multiple parameter values on the basis of a single sim...

ECG Rhythm Analysis with Expert and Learner-Generated Schemas in Novice Learners

Science.gov (United States)

Blissett, Sarah; Cavalcanti, Rodrigo; Sibbald, Matthew

2015-01-01

Although instruction using expert-generated schemas is associated with higher diagnostic performance, implementation is resource intensive. Learner-generated schemas are an alternative, but may be limited by increases in cognitive load. We compared expert- and learner-generated schemas for learning ECG rhythm interpretation on diagnostic accuracy,…

41 CFR 50-202.3 - Learners, student learners, apprentices, and handicapped workers.

Science.gov (United States)

2010-07-01

... than the minimum wage prescribed in § 50-202.2 to the same extent such employment is permitted under... Management Other Provisions Relating to Public Contracts PUBLIC CONTRACTS, DEPARTMENT OF LABOR 202-MINIMUM WAGE DETERMINATIONS Groups of Industries § 50-202.3 Learners, student learners, apprentices, and...

Bisimulation and Simulation Relations for Markov Chains

NARCIS (Netherlands)

Baier, Christel; Hermanns, H.; Katoen, Joost P.; Wolf, Verena; Aceto, L.; Gordon, A.

2006-01-01

Formal notions of bisimulation and simulation relation play a central role for any kind of process algebra. This short paper sketches the main concepts for bisimulation and simulation relations for probabilistic systems, modelled by discrete- or continuous-time Markov chains.

Model Checking Markov Chains: Techniques and Tools

NARCIS (Netherlands)

Zapreev, I.S.

2008-01-01

This dissertation deals with four important aspects of model checking Markov chains: the development of efficient model-checking tools, the improvement of model-checking algorithms, the efficiency of the state-space reduction techniques, and the development of simulation-based model-checking

Continuity Properties of Distances for Markov Processes

DEFF Research Database (Denmark)

Jaeger, Manfred; Mao, Hua; Larsen, Kim Guldstrand

2014-01-01

In this paper we investigate distance functions on finite state Markov processes that measure the behavioural similarity of non-bisimilar processes. We consider both probabilistic bisimilarity metrics, and trace-based distances derived from standard Lp and Kullback-Leibler distances. Two desirable...

Confluence reduction for Markov automata (extended version)

NARCIS (Netherlands)

Timmer, Mark; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette

Markov automata are a novel formalism for specifying systems exhibiting nondeterminism, probabilistic choices and Markovian rates. Recently, the process algebra MAPA was introduced to efficiently model such systems. As always, the state space explosion threatens the analysability of the models

Connected minds technology and today's learners

CERN Document Server

Pedrò, Francesc

2012-01-01

In all OECD countries, digital media and connectedness are integral to the lives of todays learners. It is often claimed that these learners are ""new millennium learners"", or ""digital natives"", who have different expectations about education. This book contributes to the debate about the effects of technology attachment and connectedness on todays learners, and their expectations about teaching. The book sets out to answer the following questions: Can the claim that todays students are ""new millenium learners"" or ""digital natives be sustained empirically? Is there consistent research evidence demonstrating the effects of technology on cognitive development, social values, and learning expectations? What are the implications for educational policy and practice?

The spectral method and the central limit theorem for general Markov chains

Science.gov (United States)

Nagaev, S. V.

2017-12-01

We consider Markov chains with an arbitrary phase space and develop a modification of the spectral method that enables us to prove the central limit theorem (CLT) for non-uniformly ergodic Markov chains. The conditions imposed on the transition function are more general than those by Athreya-Ney and Nummelin. Our proof of the CLT is purely analytical.

Simulation on a computer the cascade probabilistic functions and theirs relation with Markov's processes

International Nuclear Information System (INIS)

Kupchishin, A.A.; Kupchishin, A.I.; Shmygaleva, T.A.

2002-01-01

Within framework of the cascade-probabilistic (CP) method the radiation and physical processes are studied, theirs relation with Markov's processes are found. The conclusion that CP-function for electrons, protons, alpha-particles and ions are describing by unhomogeneous Markov's chain is drawn. The algorithms are developed, the CP-functions calculations for charged particles, concentration of radiation defects in solids at ion irradiation are carried out as well. Tables for CPF different parameters and radiation defects concentration at charged particle interaction with solids are given. The book consists of the introduction and two chapters: (1) Cascade probabilistic function and the Markov's processes; (2) Radiation defects formation in solids as a part of the Markov's processes. The book is intended for specialists on the radiation defects mathematical stimulation, solid state physics, elementary particles physics and applied mathematics

Semi-Markov models control of restorable systems with latent failures

CERN Document Server

Obzherin, Yuriy E

2015-01-01

Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical models of a wide class of systems for various applications. In particular, this information can be applied to build models of reliability, queuing systems, and technical control. Beginning with a brief introduction to the area, the book covers semi-Markov models for different control strategies in one-component systems, defining their stationary characteristics of reliability and efficiency, and uti

Multidimensional Learner Model In Intelligent Learning System

Science.gov (United States)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

MARKOV Model Application to Proliferation Risk Reduction of an Advanced Nuclear System

International Nuclear Information System (INIS)

Bari, R.A.

2008-01-01

The Generation IV International Forum (GIF) emphasizes proliferation resistance and physical protection (PR and PP) as a main goal for future nuclear energy systems. The GIF PR and PP Working Group has developed a methodology for the evaluation of these systems. As an application of the methodology, Markov model has been developed for the evaluation of proliferation resistance and is demonstrated for a hypothetical Example Sodium Fast Reactor (ESFR) system. This paper presents the case of diversion by the facility owner/operator to obtain material that could be used in a nuclear weapon. The Markov model is applied to evaluate material diversion strategies. The following features of the Markov model are presented here: (1) An effective detection rate has been introduced to account for the implementation of multiple safeguards approaches at a given strategic point; (2) Technical failure to divert material is modeled as intrinsic barriers related to the design of the facility or the properties of the material in the facility; and (3) Concealment to defeat or degrade the performance of safeguards is recognized in the Markov model. Three proliferation risk measures are calculated directly by the Markov model: the detection probability, technical failure probability, and proliferation time. The material type is indicated by an index that is based on the quality of material diverted. Sensitivity cases have been done to demonstrate the effects of different modeling features on the measures of proliferation resistance

Reliability analysis and prediction of mixed mode load using Markov Chain Model

International Nuclear Information System (INIS)

Nikabdullah, N.; Singh, S. S. K.; Alebrahim, R.; Azizi, M. A.; K, Elwaleed A.; Noorani, M. S. M.

2014-01-01

The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading

Markov Chain model for the stochastic behaviors of wind-direction data

International Nuclear Information System (INIS)

Masseran, Nurulkamal

2015-01-01

Highlights: • I develop a Markov chain model to describe about the stochastic and probabilistic behaviors of wind direction data. • I describe some of the theoretical arguments regarding the Markov chain model in term of wind direction data. • I suggest a limiting probabilities approach to determine a dominant directions of wind blow. - Abstract: Analyzing the behaviors of wind direction can complement knowledge concerning wind speed and help researchers draw conclusions regarding wind energy potential. Knowledge of the wind’s direction enables the wind turbine to be positioned in such a way as to maximize the total amount of captured energy and optimize the wind farm’s performance. In this paper, first-order and higher-order Markov chain models are proposed to describe the probabilistic behaviors of wind-direction data. A case study is conducted using data from Mersing, Malaysia. The wind-direction data are classified according to an eight-state Markov chain based on natural geographical directions. The model’s parameters are estimated using the maximum likelihood method and the linear programming formulation. Several theoretical arguments regarding the model are also discussed. Finally, limiting probabilities are used to determine a long-run proportion of the wind directions generated. The results explain the dominant direction for Mersing’s wind in terms of probability metrics

Markov switching of the electricity supply curve and power prices dynamics

Science.gov (United States)

Mari, Carlo; Cananà, Lucianna

2012-02-01

Regime-switching models seem to well capture the main features of power prices behavior in deregulated markets. In a recent paper, we have proposed an equilibrium methodology to derive electricity prices dynamics from the interplay between supply and demand in a stochastic environment. In particular, assuming that the supply function is described by a power law where the exponent is a two-state strictly positive Markov process, we derived a regime switching dynamics of power prices in which regime switches are induced by transitions between Markov states. In this paper, we provide a dynamical model to describe the random behavior of power prices where the only non-Brownian component of the motion is endogenously introduced by Markov transitions in the exponent of the electricity supply curve. In this context, the stochastic process driving the switching mechanism becomes observable, and we will show that the non-Brownian component of the dynamics induced by transitions from Markov states is responsible for jumps and spikes of very high magnitude. The empirical analysis performed on three Australian markets confirms that the proposed approach seems quite flexible and capable of incorporating the main features of power prices time-series, thus reproducing the first four moments of log-returns empirical distributions in a satisfactory way.

Markov chains with quasitoeplitz transition matrix

Directory of Open Access Journals (Sweden)

Alexander M. Dukhovny

1989-01-01

Full Text Available This paper investigates a class of Markov chains which are frequently encountered in various applications (e.g. queueing systems, dams and inventories with feedback. Generating functions of transient and steady state probabilities are found by solving a special Riemann boundary value problem on the unit circle. A criterion of ergodicity is established.

Evaluation of Usability Utilizing Markov Models

Science.gov (United States)

Penedo, Janaina Rodrigues; Diniz, Morganna; Ferreira, Simone Bacellar Leal; Silveira, Denis S.; Capra, Eliane

2012-01-01

Purpose: The purpose of this paper is to analyze the usability of a remote learning system in its initial development phase, using a quantitative usability evaluation method through Markov models. Design/methodology/approach: The paper opted for an exploratory study. The data of interest of the research correspond to the possible accesses of users…

Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

Science.gov (United States)

Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

2014-01-27

The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W(k

Recommendation strategies for e-learning: preliminary effects of a personal recommender system for lifelong learners

NARCIS (Netherlands)

Drachsler, Hendrik; Hummel, Hans; Van den Berg, Bert; Eshuis, Jannes; Berlanga, Adriana; Nadolski, Rob; Waterink, Wim; Boers, Nanda; Koper, Rob

2007-01-01

Drachsler, H., Hummel, H. G. K., Van den Berg, B., Eshuis, J., Berlanga, A. J., Nadolski, R. J., Waterink, W., Boers, N., & Koper, R. (2007). Recommendation strategies for e-learning: preliminary effects of personal recommender system for lifelong learners. Unpublished manuscript.

Hidden Markov models: the best models for forager movements?

Science.gov (United States)

Joo, Rocio; Bertrand, Sophie; Tam, Jorge; Fablet, Ronan

2013-01-01

One major challenge in the emerging field of movement ecology is the inference of behavioural modes from movement patterns. This has been mainly addressed through Hidden Markov models (HMMs). We propose here to evaluate two sets of alternative and state-of-the-art modelling approaches. First, we consider hidden semi-Markov models (HSMMs). They may better represent the behavioural dynamics of foragers since they explicitly model the duration of the behavioural modes. Second, we consider discriminative models which state the inference of behavioural modes as a classification issue, and may take better advantage of multivariate and non linear combinations of movement pattern descriptors. For this work, we use a dataset of >200 trips from human foragers, Peruvian fishermen targeting anchovy. Their movements were recorded through a Vessel Monitoring System (∼1 record per hour), while their behavioural modes (fishing, searching and cruising) were reported by on-board observers. We compare the efficiency of hidden Markov, hidden semi-Markov, and three discriminative models (random forests, artificial neural networks and support vector machines) for inferring the fishermen behavioural modes, using a cross-validation procedure. HSMMs show the highest accuracy (80%), significantly outperforming HMMs and discriminative models. Simulations show that data with higher temporal resolution, HSMMs reach nearly 100% of accuracy. Our results demonstrate to what extent the sequential nature of movement is critical for accurately inferring behavioural modes from a trajectory and we strongly recommend the use of HSMMs for such purpose. In addition, this work opens perspectives on the use of hybrid HSMM-discriminative models, where a discriminative setting for the observation process of HSMMs could greatly improve inference performance.

Hidden Markov models: the best models for forager movements?

Directory of Open Access Journals (Sweden)

Rocio Joo

Full Text Available One major challenge in the emerging field of movement ecology is the inference of behavioural modes from movement patterns. This has been mainly addressed through Hidden Markov models (HMMs. We propose here to evaluate two sets of alternative and state-of-the-art modelling approaches. First, we consider hidden semi-Markov models (HSMMs. They may better represent the behavioural dynamics of foragers since they explicitly model the duration of the behavioural modes. Second, we consider discriminative models which state the inference of behavioural modes as a classification issue, and may take better advantage of multivariate and non linear combinations of movement pattern descriptors. For this work, we use a dataset of >200 trips from human foragers, Peruvian fishermen targeting anchovy. Their movements were recorded through a Vessel Monitoring System (∼1 record per hour, while their behavioural modes (fishing, searching and cruising were reported by on-board observers. We compare the efficiency of hidden Markov, hidden semi-Markov, and three discriminative models (random forests, artificial neural networks and support vector machines for inferring the fishermen behavioural modes, using a cross-validation procedure. HSMMs show the highest accuracy (80%, significantly outperforming HMMs and discriminative models. Simulations show that data with higher temporal resolution, HSMMs reach nearly 100% of accuracy. Our results demonstrate to what extent the sequential nature of movement is critical for accurately inferring behavioural modes from a trajectory and we strongly recommend the use of HSMMs for such purpose. In addition, this work opens perspectives on the use of hybrid HSMM-discriminative models, where a discriminative setting for the observation process of HSMMs could greatly improve inference performance.

Markov Chain: A Predictive Model for Manpower Planning ...

African Journals Online (AJOL)

ADOWIE PERE

Keywords: Markov Chain, Transition Probability Matrix, Manpower Planning, Recruitment, Promotion, .... movement of the workforce in Jordan productivity .... Planning periods, with T being the horizon, the value of t represents a session.

Markov Chain Estimation of Avian Seasonal Fecundity

Science.gov (United States)

To explore the consequences of modeling decisions on inference about avian seasonal fecundity we generalize previous Markov chain (MC) models of avian nest success to formulate two different MC models of avian seasonal fecundity that represent two different ways to model renestin...

Data-driven Markov models and their application in the evaluation of adverse events in radiotherapy

Science.gov (United States)

Abler, Daniel; Kanellopoulos, Vassiliki; Davies, Jim; Dosanjh, Manjit; Jena, Raj; Kirkby, Norman; Peach, Ken

2013-01-01

Decision-making processes in medicine rely increasingly on modelling and simulation techniques; they are especially useful when combining evidence from multiple sources. Markov models are frequently used to synthesize the available evidence for such simulation studies, by describing disease and treatment progress, as well as associated factors such as the treatment's effects on a patient's life and the costs to society. When the same decision problem is investigated by multiple stakeholders, differing modelling assumptions are often applied, making synthesis and interpretation of the results difficult. This paper proposes a standardized approach towards the creation of Markov models. It introduces the notion of ‘general Markov models’, providing a common definition of the Markov models that underlie many similar decision problems, and develops a language for their specification. We demonstrate the application of this language by developing a general Markov model for adverse event analysis in radiotherapy and argue that the proposed method can automate the creation of Markov models from existing data. The approach has the potential to support the radiotherapy community in conducting systematic analyses involving predictive modelling of existing and upcoming radiotherapy data. We expect it to facilitate the application of modelling techniques in medical decision problems beyond the field of radiotherapy, and to improve the comparability of their results. PMID:23824126

Data-driven Markov models and their application in the evaluation of adverse events in radiotherapy

International Nuclear Information System (INIS)

Abler, Daniel; Kanellopoulos, Vassiliki; Dosanjh, Manjit; Davies, Jim; Peach, Ken; Jena, Raj; Kirkby, Norman

2013-01-01

Decision-making processes in medicine rely increasingly on modelling and simulation techniques; they are especially useful when combining evidence from multiple sources. Markov models are frequently used to synthesize the available evidence for such simulation studies, by describing disease and treatment progress, as well as associated factors such as the treatment's effects on a patient's life and the costs to society. When the same decision problem is investigated by multiple stakeholders, differing modelling assumptions are often applied, making synthesis and interpretation of the results difficult. This paper proposes a standardized approach towards the creation of Markov models. It introduces the notion of 'general Markov models', providing a common definition of the Markov models that underlie many similar decision problems, and develops a language for their specification. We demonstrate the application of this language by developing a general Markov model for adverse event analysis in radiotherapy and argue that the proposed method can automate the creation of Markov models from existing data. The approach has the potential to support the radiotherapy community in conducting systematic analyses involving predictive modelling of existing and upcoming radiotherapy data. We expect it to facilitate the application of modelling techniques in medical decision problems beyond the field of radiotherapy, and to improve the comparability of their results. (author)

Learning classifier systems with memory condition to solve non-Markov problems

OpenAIRE

Zang, Zhaoxiang; Li, Dehua; Wang, Junying

2012-01-01

In the family of Learning Classifier Systems, the classifier system XCS has been successfully used for many applications. However, the standard XCS has no memory mechanism and can only learn optimal policy in Markov environments, where the optimal action is determined solely by the state of current sensory input. In practice, most environments are partially observable environments on agent's sensation, which are also known as non-Markov environments. Within these environments, XCS either fail...

Stochastic Dynamics through Hierarchically Embedded Markov Chains.

Science.gov (United States)

Vasconcelos, Vítor V; Santos, Fernando P; Santos, Francisco C; Pacheco, Jorge M

2017-02-03

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects-such as mutations in evolutionary dynamics and a random exploration of choices in social systems-including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

Exact solution of the hidden Markov processes

Science.gov (United States)

Saakian, David B.

2017-11-01

We write a master equation for the distributions related to hidden Markov processes (HMPs) and solve it using a functional equation. Thus the solution of HMPs is mapped exactly to the solution of the functional equation. For a general case the latter can be solved only numerically. We derive an exact expression for the entropy of HMPs. Our expression for the entropy is an alternative to the ones given before by the solution of integral equations. The exact solution is possible because actually the model can be considered as a generalized random walk on a one-dimensional strip. While we give the solution for the two second-order matrices, our solution can be easily generalized for the L values of the Markov process and M values of observables: We should be able to solve a system of L functional equations in the space of dimension M -1 .

Discrete-time semi-Markov modeling of human papillomavirus persistence

Science.gov (United States)

Mitchell, C. E.; Hudgens, M. G.; King, C. C.; Cu-Uvin, S.; Lo, Y.; Rompalo, A.; Sobel, J.; Smith, J. S.

2011-01-01

Multi-state modeling is often employed to describe the progression of a disease process. In epidemiological studies of certain diseases, the disease state is typically only observed at periodic clinical visits, producing incomplete longitudinal data. In this paper we consider fitting semi-Markov models to estimate the persistence of human papillomavirus (HPV) type-specific infection in studies where the status of HPV type(s) is assessed periodically. Simulation study results are presented indicating the semi-Markov estimator is more accurate than an estimator currently used in the HPV literature. The methods are illustrated using data from the HIV Epidemiology Research Study (HERS). PMID:21538985

[Application of Markov model in post-marketing pharmacoeconomic evaluation of traditional Chinese medicine].

Science.gov (United States)

Wang, Xin; Su, Xia; Sun, Wentao; Xie, Yanming; Wang, Yongyan

2011-10-01

In post-marketing study of traditional Chinese medicine (TCM), pharmacoeconomic evaluation has an important applied significance. However, the economic literatures of TCM have been unable to fully and accurately reflect the unique overall outcomes of treatment with TCM. For the special nature of TCM itself, we recommend that Markov model could be introduced into post-marketing pharmacoeconomic evaluation of TCM, and also explore the feasibility of model application. Markov model can extrapolate the study time horizon, suit with effectiveness indicators of TCM, and provide measurable comprehensive outcome. In addition, Markov model can promote the development of TCM quality of life scale and the methodology of post-marketing pharmacoeconomic evaluation.

A Martingale Decomposition of Discrete Markov Chains

DEFF Research Database (Denmark)

Hansen, Peter Reinhard

We consider a multivariate time series whose increments are given from a homogeneous Markov chain. We show that the martingale component of this process can be extracted by a filtering method and establish the corresponding martingale decomposition in closed-form. This representation is useful fo...

Efficient Modelling and Generation of Markov Automata

NARCIS (Netherlands)

Koutny, M.; Timmer, Mark; Ulidowski, I.; Katoen, Joost P.; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette

This paper introduces a framework for the efficient modelling and generation of Markov automata. It consists of (1) the data-rich process-algebraic language MAPA, allowing concise modelling of systems with nondeterminism, probability and Markovian timing; (2) a restricted form of the language, the