Relevant bibliographies by topics / Wrong models

Academic literature on the topic 'Wrong models'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Wrong models"

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So, Richard Jean. "“All Models Are Wrong”." PMLA/Publications of the Modern Language Association of America 132, no. 3 (May 2017): 668–73. http://dx.doi.org/10.1632/pmla.2017.132.3.668.

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Several years ago, the first thing i learned in my introductory statistics class was the following declaration, which the instructor had written in capital letters on the blackboard: “all models are wrong.” Models are statistical, graphic, or physical objects, and their primary quality is that they can be manipulated. Scientists and social scientists use them to think about the social or natural worlds and to represent those worlds in a simplified manner. Statistical models, which dominate the social sciences, particularly in economics, are typically equations with response and predictor variables. Specifically, a researcher seeks to understand some social phenomenon, such as the relation between students' scores on a math test and how many hours the students spent preparing for the exam. To predict or describe this relation, the researcher constructs a quantitative model with quantitative inputs (the number of hours each student spent studying) and outputs (each student's test score). The researcher hopes that the number of hours a student spent preparing for the exam will correlate with the student's score. If it does, this quantified relation can help describe the overall dynamics of test taking.
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Shafer, Steven L. "All Models Are Wrong." Anesthesiology 116, no. 2 (February 1, 2012): 240–41. http://dx.doi.org/10.1097/aln.0b013e318242a4a7.

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Hickerson, Michael J. "All models are wrong." Molecular Ecology 23, no. 12 (June 2014): 2887–89. http://dx.doi.org/10.1111/mec.12794.

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Steelman, Brandon. "Trump: polls right, models wrong." Nature 540, no. 7631 (November 30, 2016): 39. http://dx.doi.org/10.1038/540039e.

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Zilla, Peter, Deon Bezuidenhout, and Paul Human. "Prosthetic vascular grafts: Wrong models, wrong questions and no healing." Biomaterials 28, no. 34 (December 2007): 5009–27. http://dx.doi.org/10.1016/j.biomaterials.2007.07.017.

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Grabinski, Michael, and Galiya Klinkova. "Wrong Use of Averages Implies Wrong Results from Many Heuristic Models." Applied Mathematics 10, no. 07 (2019): 605–18. http://dx.doi.org/10.4236/am.2019.107043.

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Bakker, Mark. "Are All Models Wrong? Absolutely Not." Groundwater 51, no. 3 (February 26, 2013): 313. http://dx.doi.org/10.1111/gwat.12037.

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Parnell, Laura K. S. "Wound Models: Wrong, Right, or Irrelevant?" Advances in Wound Care 8, no. 12 (December 1, 2019): 644. http://dx.doi.org/10.1089/wound.2019.1099.

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Kamb, Alexander. "What's wrong with our cancer models?" Nature Reviews Drug Discovery 4, no. 2 (February 2005): 161–65. http://dx.doi.org/10.1038/nrd1635.

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Remington, Patrick L. "All Models Are Wrong; Some Are Useful." American Journal of Public Health 107, no. 8 (August 2017): e28-e28. http://dx.doi.org/10.2105/ajph.2017.303892.

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Dissertations / Theses on the topic "Wrong models"

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Mendoza, Waldo. "IS-LM Stability Revisited: Samuelson was Right, Modigliani was Wrong." Economía, 2015. http://repositorio.pucp.edu.pe/index/handle/123456789/116799.

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In Hicks’s IS-LM model, where it is assumed that production is determined in the goods marketand the interest rate is determined in the money market, when the marginal propensity to spend is greater than one, the IS has a positive slope. Modigliani (1944), Varian (1977) and Sargent (1987) determined that in this special case the IS-LM model is stable when the LM slope isgreater than the IS.In line with Samuelson (1941), this article shows that in this case the model is stable when the IS slope is greater than the LM slope. However, in this stable case the model does not have a useful economic meaning.One solution to this theoretical problem is to abandon the Keynesian adjustment mechanism and replace it with the Classical mechanism where the interest rate is determined in the goods market and production is determined in the money market. In this case, the IS-LM model is stable when the LM is steeper than the IS.
En el modelo IS-LM de Hicks, en el que se asume que la producción se determina en el mercado de bienes y la tasa de interés en el mercado de dinero, cuando la propensión marginal a gastar es mayor que uno, la IS tiene pendiente positiva. Modigliani (1944), Varian (1977) y Sargent (1987), determinaron que en este caso especial el modelo IS-LM es estable cuando la pendiente de la LM es mayor que la de la IS.En línea con Samuelson (1941), este artículo muestra que en este caso especial el modelo es estable cuando la pendiente de la IS es mayor que la de la LM. Sin embargo, en este caso estable, el modelo no tiene un significado económico útil.Una solución a este problema teórico es abandonar el mecanismo de ajuste keynesiano y reemplazarlo por el mecanismo clásico, donde la tasa de interés se determina en el mercado de bienes y la producción en el mercado de dinero. En este caso el modelo IS-LM es estable cuando la LM es más empinada que la IS.
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Gstach, Dieter. "Data Envelopment Analysis in a Stochastic Setting: The right answer from the wrong model?" Inst. für Volkswirtschaftstheorie und -politik, WU Vienna University of Economics and Business, 1994. http://epub.wu.ac.at/6304/1/WP_29.pdf.

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Data envelopment analysis (DEA) is compared to stochastic production function estimation (SPFE) in a noisy setting. The statistic of interest is the average efficiency estimator. Monte-Carlo simulations show that the mean squared error of the DEA-estimator even for considerable noise remains below the MSE of the SPFE analogue. A bootstrapping approach is designed to get some first-step statistical underpinning of this DEA average efficiency estimator. The coverage of the bootstrapping approximation to the distribution of this estimator is shown to be fairly good.
Series: Department of Economics Working Paper Series
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Potter, Kevin Whitman. "When You are Confident that You are Wrong: Response Reversals and the Expanded Poisson Race Model." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1321454142.

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Sosa, Nicholas. "Looking for Meaning in All the Wrong Places: The Search for Meaning After Direct and Indirect Meaning Compensation." Ohio University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1486982633785334.

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Ecker, Kreske. "DOES IT MATTER HOW WE GO WRONG? : The role of model misspecification and study design in assessing the performance of doubly robust estimators." Thesis, Umeå universitet, Statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136286.

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This thesis concerns doubly robust (DR) estimation in missing data contexts. Previous research is not unanimous as to which estimators perform best and in which situations DR is to be preferred over other estimators. We observe that the conditions surrounding comparisons of DR- and other estimators vary between dierent previous studies. We therefore focus on the effects of three distinct aspects of study design on the performance of one DR-estimator in comparison to outcome regression (OR). These aspects are sample size, the way in which models are misspecified, and the degree of association between the covariates and propensities. We find that while there are no drastic eects of the type of model misspecication, all three aspects do affect how DR compares to OR. The results can be used to better understand the divergent conclusions of previous research.
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Harnew, Samuel T. "A measurement of D-mixing in wrong sign D° K⁺π⁻π⁺π⁻ decays to provide input to a model-independent determination of the CKM phase ϓ." Thesis, University of Bristol, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.689691.

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Lani, James Anthony. "Improving a Marker-Based System to Rate Assimilation of Problematic Experiences." Miami University / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=miami1055936557.

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El-Khatib, Mayar. "Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement." Thesis, 2010. http://hdl.handle.net/10012/5741.

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While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond.
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Wrogemann, Gail Cynthia. "Intergroup relations in organizations." 2002. http://hdl.handle.net/10500/16500.

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Books on the topic "Wrong models"

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Svensson, Lars E. O. Targeting rules vs. instrument rules for monetary policy: What is wrong with McCallum and Nelson? Cambridge, Mass: National Bureau of Economic Research, 2004.

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Svensson, Lars E. O. Targeting rules vs. instrument rules for monetary policy: What is wrong with McCallum and Nelson? Cambridge, MA: National Bureau of Economic Research, 2004.

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What's wrong with my mouse?: Behavioral phenotyping of transgenic and knockout mice. 2nd ed. Hoboken, NJ: Wiley-Interscience, 2007.

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West, Bruce J. Where medicine went wrong: Rediscovering the path to complexity. Hackensack, NJ: World Scientific, 2007.

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Where medicine went wrong: Rediscovering the path to complexity. Hackensack, NJ: World Scientific, 2007.

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Card, David E. Dropout and enrollment trends in the Post-War period: What went wrong in the 1970s? Cambridge, MA: National Bureau of Economic Research, 2000.

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Getting it wrong: How faulty monetary statistics undermine the Fed, the financial system, and the economy. Cambridge, Mass: MIT Press, 2012.

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Ananat, Elizabeth Oltmans. The wrong side(s) of the tracks: Estimating the causal effects of racial segregation on city outcomes. Cambridge, Mass: National Bureau of Economic Research, 2007.

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Bound, John. What went wrong?: The erosion of relative earnings and employment among young black men in the 1980s. Cambridge, MA: National Bureau of Economic Research, 1991.

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Wainer, Howard. Estimating ability with the wrong model. Brooks Air Force Base, Tex: Air Force Human Resources Laboratory, Air Force Systems Command, 1985.

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Book chapters on the topic "Wrong models"

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Joseph, Jennie. "There’s Something Wrong Here." In Birthing Models on the Human Rights Frontier, 131–44. Abingdon, Oxon ; New York, NY : Routledge, 2021.: Routledge, 2020. http://dx.doi.org/10.4324/9781003088783-7.

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Hennig, Christian. "How Wrong Models Become Useful — and Correct Models Become Dangerous." In Between Data Science and Applied Data Analysis, 235–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-18991-3_27.

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Berk, Richard A., Lawrence Brown, Edward George, Emil Pitkin, Mikhail Traskin, Kai Zhang, and Linda Zhao. "What You Can Learn from Wrong Causal Models." In Handbooks of Sociology and Social Research, 403–24. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6094-3_19.

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Molnar, Christoph, Gunnar König, Julia Herbinger, Timo Freiesleben, Susanne Dandl, Christian A. Scholbeck, Giuseppe Casalicchio, Moritz Grosse-Wentrup, and Bernd Bischl. "General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models." In xxAI - Beyond Explainable AI, 39–68. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04083-2_4.

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AbstractAn increasing number of model-agnostic interpretation techniques for machine learning (ML) models such as partial dependence plots (PDP), permutation feature importance (PFI) and Shapley values provide insightful model interpretations, but can lead to wrong conclusions if applied incorrectly. We highlight many general pitfalls of ML model interpretation, such as using interpretation techniques in the wrong context, interpreting models that do not generalize well, ignoring feature dependencies, interactions, uncertainty estimates and issues in high-dimensional settings, or making unjustified causal interpretations, and illustrate them with examples. We focus on pitfalls for global methods that describe the average model behavior, but many pitfalls also apply to local methods that explain individual predictions. Our paper addresses ML practitioners by raising awareness of pitfalls and identifying solutions for correct model interpretation, but also addresses ML researchers by discussing open issues for further research.
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Doyle, Colin. "All Models Are Wrong, But Are Risk Assessments Useful?" In Handbook on Pretrial Justice, 324–35. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003149842-21.

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Tolk, Andreas. "Learning Something Right from Models That Are Wrong: Epistemology of Simulation." In Concepts and Methodologies for Modeling and Simulation, 87–106. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15096-3_5.

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Stenner, A. Jackson, Ivan Horabin, Dean R. Smith, and Malbert Smith. "Most Comprehension Tests Do Measure Reading Comprehension: A Response to McLean and Goldstein." In Explanatory Models, Unit Standards, and Personalized Learning in Educational Measurement, 57–62. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3747-7_5.

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AbstractThere is nothing wrong with the NAEP reading exercises, the sampling design, or the NAEP Reading Proficiency Scale, these authors maintain. But adding a rich criterion-based frame of reference to the scale should yield an even more useful tool for shaping U.S. educational policy.
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Strand, Roger, and Dominique Chu. "Crossing the Styx: If Precision Medicine Were to Become Exact Science." In Human Perspectives in Health Sciences and Technology, 133–54. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92612-0_9.

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AbstractThe term “precision medicine” is used to denote existing practices as well as how medical research and practice are imagined to become in the future. One important element of the imaginaries of precision medicine is the development of systems biology and computational models with the promise of numerical precision and conceptual rigour. If precision medicine were to become an exact science that relies on computational models, it might increase precision in diagnosis and treatment, specifying the right drug to the right patient at the right time. It should be noted, though, that computational models require explicit specification of the properties and boundaries of the system to be modelled, whereas cells, tissues and patients are predominantly open systems in their natural state. Accordingly, such models risk being precisely wrong instead of approximately right. Right and wrong, however, are value judgements that depend upon the aims and scope of the scientific and medical enterprise. In order for medicine to become an exact science, cells, tissues and patients would have to be reconceived and/or reconfigured as relatively closed systems with relatively deterministic behaviour. The realization of precision medicine as an exact science may thus be accompanied by a transition from a world of complex natural life to a world of reduced life or a simple delay of death; a transition to be likened with the crossing of the Styx.
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Pilyasov, Alexander Nickolaevich, and Valeriy Aleksandrovich Kibenko. "The Phenomenon of Entrepreneurship in Reindeer Husbandry in Yamal: Assessment of the Situation, Paradoxes, and Contradictions." In Reindeer Husbandry, 255–78. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17625-8_10.

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AbstractThe chapter considers the development of domestic reindeer herding in the Yamal-Nenets Autonomous Region over the past 30 years in terms of an entrepreneurial paradigm. Individual reindeer herding families own almost 60% of all domestic reindeer in the region. The chapter describes two types of nomadic entrepreneurs: economically independent and those relying on state support as well as differences in their behavior patterns, cultural values, and nomadic routes. Two reindeer herding models are presented: the ‘meat model’ of the Yamalsky district and the ‘antler model’ of the Tazovsky and Priuralsky districts in Yamal. Both models determine the differences in terms of size, dynamics and structure of the herd, length of nomadic routes, structure of production income. Unlike the dominant point of view blaming irresponsible reindeer herders for the depletion of pastures, the authors of the article see the problem as an institutional one – the result of public policies that created wrong incentives for reindeer herding entrepreneurs in recent decades. This policy transferred them to the position of hired herders equal to the state workers. The authors propose reforms in Yamal reindeer herding that will ensure a decisive transition to an entrepreneurial model in reindeer husbandry and an algorithm for the reforms in the state support system.
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Groce, Alex, and Willem Visser. "What Went Wrong: Explaining Counterexamples." In Model Checking Software, 121–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44829-2_8.

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Conference papers on the topic "Wrong models"

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Hand, David J. "Mismatched models, wrong results, and dreadful decisions." In the 15th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1557019.1557021.

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Delatte, Norb. "Using Models in Forensic Engineering—All Models Are Wrong, but Some Are Useful." In Ninth Congress on Forensic Engineering. Reston, VA: American Society of Civil Engineers, 2022. http://dx.doi.org/10.1061/9780784484548.059.

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Comastri, Andrea. "What’s wrong with AGN models for the X-ray background?" In X-RAY ASTRONOMY: Stellar Endpoints,AGN, and the Diffuse X-ray Background. AIP, 2001. http://dx.doi.org/10.1063/1.1434620.

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Haneberg, William. "MODELS HERE, MODELS THERE; MODELS, MODELS EVERYWHERE OR: HOW I LEARNED TO STOP WORRYING AND LOVE BEING WRONG." In GSA Connects 2022 meeting in Denver, Colorado. Geological Society of America, 2022. http://dx.doi.org/10.1130/abs/2022am-380643.

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"PRECISELY WRONG OR ROUGHLY RIGHT? AN EVALUATION OF DEVELOPMENT VIABILITY MODELS." In 17th Annual European Real Estate Society Conference: ERES Conference 2010. ERES, 2010. http://dx.doi.org/10.15396/eres2010_305.

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Keane, Kevin R., and Jason J. Corso. "The Wrong Tool for Inference - A Critical View of Gaussian Graphical Models." In 7th International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006644604700477.

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Tsioptsias, Naoum, Antuela Tako, and Stewart Robinson. "An Exploratory Study on the Use of "Wrong" Simulation Models in Practice." In SW20: The OR Society Simulation Workshop. The OR Society, 2020. http://dx.doi.org/10.36819/sw20.035.

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Tsioptsias, Naoum, Antuela Tako, and Stewart Robinson. "An Exploratory Study on the Uses of "Wrong" Simulation Models in Practice." In SW21 The OR Society Simulation Workshop. Operational Research Society, 2021. http://dx.doi.org/10.36819/sw21.018.

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Gasparini, Nicole M., Katherine R. Barnhart, Adam M. Forte, and Nathan J. Lyons. "ALL MODELS ARE WRONG, OFTEN IN DIFFERENT WAYS: AN INTER-COMPARISON STUDY OF LANDSCAPE EVOLUTION MODELS." In GSA Annual Meeting in Phoenix, Arizona, USA - 2019. Geological Society of America, 2019. http://dx.doi.org/10.1130/abs/2019am-338746.

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Brigo, Damiano, Thomas Hvolby, and Frédéric Vrins. "Wrong-Way Risk Adjusted Exposure: Analytical Approximations for Options in Default Intensity Models." In Innovations in Insurance, Risk- and Asset Management. WORLD SCIENTIFIC, 2018. http://dx.doi.org/10.1142/9789813272569_0002.

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Reports on the topic "Wrong models"

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Nelson, Daniel, and Dean Foster. Filtering and Forecasting with Misspecified Arch Models II: Making the Right Forecast with the Wrong Model. Cambridge, MA: National Bureau of Economic Research, December 1992. http://dx.doi.org/10.3386/t0132.

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Stiglitz, Joseph. Where Modern Macroeconomics Went Wrong. Cambridge, MA: National Bureau of Economic Research, September 2017. http://dx.doi.org/10.3386/w23795.

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Wainer, H., and D. Thissen. Estimating Ability with the Wrong Model. Fort Belvoir, VA: Defense Technical Information Center, April 1985. http://dx.doi.org/10.21236/ada154071.

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Hernández, Juan, and Juan Santaella. How to repay the after-COVID-19 public debt?: The case of Colombia. Inter-American Development Bank, May 2022. http://dx.doi.org/10.18235/0004248.

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The COVID-19 pandemic produced a shock to public finances throughout the world. In the case of Colombia, the public debt to GDP ratio increased from 39.8% to 65.0%. We use a two-country neoclassical general equilibrium model to determine which one-shot tax reforms make the new debt level sustainable. Our analysis shows that Colombia was on the wrong side of the Laffer curve for capital and labor income taxes before the crisis and hence would need to reduce those taxes to repay its current debt. Specifically, reducing the capital tax by four percentage points and the labor tax by three percentage points restores sustainability. In contrast, the analysis suggests that the economy is on the upward-sloping side of the Laffer curve for the consumption tax. An increase of 10 percentage points in the consumption tax generates a future path of primary surpluses big enough to repay the post-COVID level of debt. The results suggest that behavioral changes and general equilibrium effects are sizeable. Therefore, ignoring them will bias fiscal consolidation analysis.
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Lichter, Amnon, David Obenland, Nirit Bernstein, Jennifer Hashim, and Joseph Smilanick. The role of potassium in quality of grapes after harvest. United States Department of Agriculture, October 2015. http://dx.doi.org/10.32747/2015.7597914.bard.

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Objectives: The objectives of the proposal were to study how potassium (K) enters the berry and in what tissues it accumulates, to determine what is the sensitive phenological stage that is responsive to K, to study the influence of K on sugar translocation, to determine if K has effects on expression of genes in source and sink organs and to study applied aspects of the responses to K at the vineyard level. During the research it was realized that K acts externally so a major part of the original objectives had to be deserted and new ones, i.e. the role of K in enhancing water loss from the berry, had to be developed. In addition, the US partners developed practical objectives of understanding the interaction of K application and water deficit as well as application of growth regulators. Background: In our preliminary data we showed that application of K at mid-ripening enhanced sugar accumulation of table grapes. This finding is of major implications to both early and late harvested grapes and it was essential to understand the mode of action of this treatment. Our major hypothesis was that K enters the berry and by that increases sugar translocation into the berry. In addition it was important to cover practical issues of the application which may influence its efficacy and its reproducibility. Conclusions: The major conclusion from the research was that our initial hypothesis was wrong. Mineral analysis of pulp tissue indicated that upon application of K there was a significant increase in most of the major minerals. Subsequently, we developed a new hypothesis that K acts by increasing the water loss from the berry. In vitro studies of K-treated berries corroborated this hypothesis showing greater weight-loss of treated berries. This was not necessarily expressed in the vineyard as in some experiments berry weight remained unchanged, suggesting that the vine compensated for the enhanced water loss. Importantly, we also discovered that the efficacy of different K salts was strongly correlated to the pH of the salt solution: basic K salts had better efficacy than neutral or acidic salts and modifying the pH of the same salt changed its efficacy. It was therefore suggested that K changes the properties of the cuticle making it more susceptible to water loss. Of the practical aspects it was found that application of K to the clusters was sufficient to trigger its affect and that dual application of K had a stronger effect than single application. With regard to timing, it was realized that application of K after veraison was affective and the berries responded also when ripe. While the effect of K application was significant at harvest, it was mostly insignificant one week after application, suggesting that prolonged exposure to K was required. Implications: The scientific implications of the study are that the external mineral composition of the berry may have a significant role in sugar accumulation and that water loss may have an important role in sugar accumulation in grapes. It is not entirely clear how K modulates the cuticle but according to the literature its incorporation into the cuticle may increase its polarity and facilitate generation of "water bridges" between the flesh and the environment. The practical implications of this study are very significant because realizing the mode of action of K can facilitate a much more efficient application strategy. For example, it can be understood that sprays must be directed to the clusters rather than the whole vines and it can be predicted that the length of exposure is important. Also, by increasing the pH of simple K salts, the efficacy of the treatment can be enhanced, saving in the costs of the treatment. Finally, the ability of grape growers to apply K in a safe and knowledgeable way can have significant impact on the length of the season of early grape cultivars and improve the flavor of high grape yields which may otherwise have compromised sugar levels.
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