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Operations Research, Systems Engineering and Industrial Engineering Commons™
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- VALUE OF INFORMATION AND PORTFOLIO DECISION ANALYSIS (5)
- PROBABILISTIC MODELING (4)
- PROBABLITY ASSESSMENT, BIASES, AND SCORING RULES (4)
- DECISION ANALYSIS EDUCATION (3)
- Decision analysis (3)
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- Dependence (2)
- Maximum entropy (2)
- Scoring rules (2)
- Value of information (2)
- Approximations (1)
- Calibration (1)
- Copulas (1)
- DISCRETIZATION (1)
- Decision trees (1)
- Discretization (1)
- Dynamic programming (1)
- Markov processes (1)
- Options (1)
- Probability assessment (1)
- Seismic (1)
- Simulation (1)
- UTILITY THEORY (1)
- Utility theory (1)
Articles 1 - 14 of 14
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Generating A Random Collection Of Discrete Joint Probability Distributions Subject To Partial Information, Luis V. Montiel, J. Eric Bickel
Generating A Random Collection Of Discrete Joint Probability Distributions Subject To Partial Information, Luis V. Montiel, J. Eric Bickel
Eric Bickel
In this paper, we develop a practical and flexible methodology for generating a random collection of discrete joint probability distributions, subject to a specified information set, which can be expressed as a set of linear constraints (e.g., marginal assessments, moments, or pairwise correlations). Our approach begins with the construction of a polytope using this set of linear constraints. This polytope defines the set of all joint distributions that match the given information; we refer to this set as the “truth set.”We then implement aMonte Carlo procedure, the Hit-and- Run algorithm, to sample points uniformly from the truth set. Each sampled …
Scoring Rules And Decision Analysis Education, J. Eric Bickel
Scoring Rules And Decision Analysis Education, J. Eric Bickel
Eric Bickel
Experiential learning is perhaps the most effective way to teach. One example is the scoring procedure used for exams in some decision analysis programs. Under this grading scheme, students take a multiple-choice exam, but rather than simply marking which answer they think is correct, they must assign a probability to each possible answer. The exam is then scored with a special scoring rule, under which students’ best strategy is to avoid guessing and instead assign their true beliefs. Such a scoring function is known as a strictly proper scoring rule. In this paper, we discuss several different scoring rules and …
Discretization, Simulation, And Swanson’S (Inaccurate) Mean, J. Eric Bickel
Discretization, Simulation, And Swanson’S (Inaccurate) Mean, J. Eric Bickel
Eric Bickel
Swanson’s Mean (SM) is heavily used within the oil and gas industry to approximate continuous probability distributions such as the lognormal. In this paper, we document the errors induced by this practice, which, as we show, has no theoretical justification for any distribution other than the normal. In parallel, we review methods to discretize continuous distributions and compare these methods to Monte Carlo simulation. We demonstrate that the best discretization methods have an accuracy equivalent to that of tens of thousands of Monte Carlo trials.
Comparing Nws Pop Forecasts To Third-Party Providers, J. Eric Bickel, Eric Floehr, Seong Dae Kim
Comparing Nws Pop Forecasts To Third-Party Providers, J. Eric Bickel, Eric Floehr, Seong Dae Kim
Eric Bickel
In this paper, the authors verify probability of precipitation (PoP) forecasts provided by the National Weather Service (NWS), The Weather Channel (TWC), and CustomWeather (CW). The n-day-ahead forecasts, where n ranges from 1 to 3 for the NWS, from 1 to 9 for TWC, and from 1 to 14 for CW, are analyzed. The dataset includes almost 13 million PoP forecasts, or about 500 000 PoPs per provider per day of lead time. Data were collected over a 2-yr period (1 November 2008–31 October 2010) at 734 observation stations across the contiguous United States. In addition to verifying these PoP …
Roads Or Radar: The Tradeoff Between Investments In Infrastructure And Forecasting When Facing Hurricane Risk, Eric Bickel, Seong Dae Kim
Roads Or Radar: The Tradeoff Between Investments In Infrastructure And Forecasting When Facing Hurricane Risk, Eric Bickel, Seong Dae Kim
Eric Bickel
When faced with a significant risk, society must decide howmuch to invest in prediction and response. For example, in the face of hurricane risk how much should we invest in better forecasting versus increased evacuation speed? To address this need, we develop a Markov decision processes model to analyze the interaction between the emergency response system and the emergency forecasting system. The model shows the tradeoff between the two investments given a budget limit. In addition, the research indicates that the superiority of the investment changes sharply by the lead time.
On The Decision To Take A Pitch, J. Eric Bickel
On The Decision To Take A Pitch, J. Eric Bickel
Eric Bickel
Baseball is a highly strategic game, with decisions being made almost continuously. In this paper, we analyze the decision to have the batter take a pitch, which means that he does not swing at the pitch under any circumstances—even if it is easily hittable. Why would a batter do this? Using decision-theoretic reasoning, we determine under what circumstances such a decision is good. We find that in some cases, taking pitches deterministically dominates not taking.
Verification Of The Weather Channel Probability Of Precipitation Forecasts, Eric Bickel, Seong Kim
Verification Of The Weather Channel Probability Of Precipitation Forecasts, Eric Bickel, Seong Kim
Eric Bickel
The Weather Channel (TWC) is a leading provider of weather information to the general public. In this paper the reliability of their probability of precipitation (PoP) forecasts over a 14-month period at 42 locations across the United States is verified. It is found that PoPs between 0.4 and 0.9 are well calibrated for near-term forecasts. However, overall TWC PoPs are biased toward precipitation, significantly so during the warm season (April–September). PoPs lower than 0.3 and above 0.9 are not well calibrated, a fact that can be explained by TWC’s forecasting procedure. In addition, PoPs beyond a 6-day lead time are …
The Relationship Between Perfect And Imperfect Information In A Risk-Sensitive Two-Action Problem, Eric Bickel
The Relationship Between Perfect And Imperfect Information In A Risk-Sensitive Two-Action Problem, Eric Bickel
Eric Bickel
No abstract provided.
Quantifying 3d Land Seismic Reliability And Value, J. Eric Bickel, Richard L. Gibson, Duane A. Mcvay, Stephen Pickering, John Waggoner
Quantifying 3d Land Seismic Reliability And Value, J. Eric Bickel, Richard L. Gibson, Duane A. Mcvay, Stephen Pickering, John Waggoner
Eric Bickel
Seismic data provide essential information for guiding reservoir development. Improvements in data quality hold the promise of improving performance even further, provided that the value of these data exceed their cost. Previous work has demonstrated value-of-information (VoI) methods to quantify the value of seismic data. In these examples, seismic accuracy was obtained via expert assessment instead of being based on geophysical quantities. The modeled seismic information was not representative of any quantity that would be observed in a seismic image. Here we apply a more general VoI model that includes multiple targets, budgetary constraints, and quantitative models relating post-stack seismic …
Modeling Dependence Among Geologic Risks In Sequential Exploration Decisions, J. Eric Bickel, James E. Smith
Modeling Dependence Among Geologic Risks In Sequential Exploration Decisions, J. Eric Bickel, James E. Smith
Eric Bickel
Prospects in a common basin are likely to share geologic features. For example, if hydrocarbons are found at one location, they may be more likely to be found at other nearby locations. When making drilling decisions, we should be able to exploit this dependence and use drilling results from one location to make more informed decisions about other nearby prospects. Moreover, we should consider these informational synergies when evaluating multi-prospect exploration opportunities. In this paper, we describe an approach for modeling the dependence among prospects and determining an optimal drilling strategy that takes this information into account. We demonstrate this …
Some Comparisons Among Quadratic, Spherical, And Logarithmic Scoring Rules, Eric Bickel
Some Comparisons Among Quadratic, Spherical, And Logarithmic Scoring Rules, Eric Bickel
Eric Bickel
Strictly proper scoring rules continue to play an important role in probability assessment. Although many such rules have been developed, relatively little guidance exists as to which rule is the most appropriate. In this paper, we discuss two important properties of quadratic, spherical, and logarithmic scoring rules. From an ex post perspective, we compare their rank order properties and conclude that both quadratic and spherical scoring perform poorly in this regard, relative to logarithmic. Second, from an ex ante perspective, we demonstrate that in many situations, logarithmic scoring is the method least affected by a nonlinear utility function. These results …
Optimal Sequential Exploration: A Binary Learning Model, J. Eric Bickel, James E. Smith
Optimal Sequential Exploration: A Binary Learning Model, J. Eric Bickel, James E. Smith
Eric Bickel
In this paper, we develop a practical and flexible framework for evaluating sequential exploration strategies in the case where the exploration prospects are dependent. Our interest in this problem was motivated by an oil exploration problem, and our approach begins with marginal assessments for each prospect (e.g., what is the probability that the well is wet?) and pairwise assessments of the dependence between prospects (e.g., what is the probability that both wells i and j are wet?). We then use information-theoretic methods to construct a full joint distribution for all outcomes from these marginal and pairwise assessments. This joint distribution …
Some Determinants Of Corporate Risk Aversion, Eric Bickel
Some Determinants Of Corporate Risk Aversion, Eric Bickel
Eric Bickel
In this paper we roughly quantify the degree of risk aversion induced by three rationales for corporate risk management: the cost of financial distress, costly external finance, and the principal-agent relationship between shareholders and management. In so doing, we provide a foundation for the use of corporate utility functions. However, we are unable to fully support the degree of risk aversion reported in the decision analysis literature. Specifically, financial distress and costly external finance appear to induce relatively little risk aversion, while principal-agent concerns lend only partial support to published corporate risk tolerance guidelines.
Teaching Decision Making With Baseball Examples, J. Eric Bickel
Teaching Decision Making With Baseball Examples, J. Eric Bickel
Eric Bickel
Sports examples can be wonderful vehicles for teaching OR/MS concepts. Baseball is particularly well suited to teaching statistics/probability, Markov decision processes, and decision analysis. This paper details a baseball example I developed to teach fundamental decision making skills. This example has been used successfully to teach decision making to undergraduates and graduates in technical and non-technical disciplines. It has also been used effectively in industry for training new MBAs and seasoned executives.