Literatura académica sobre el tema "Expectational Model"
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Artículos de revistas sobre el tema "Expectational Model"
Heinemann, Maik. "CONVERGENCE OF ADAPTIVE LEARNING AND EXPECTATIONAL STABILITY: THE CASE OF MULTIPLE RATIONAL-EXPECTATIONS EQUILIBRIA". Macroeconomic Dynamics 4, n.º 3 (septiembre de 2000): 263–88. http://dx.doi.org/10.1017/s1365100500016011.
Texto completoKoustas, Zisimos. "Some model-based tests of expectational rationality". Atlantic Economic Journal 17, n.º 2 (junio de 1989): 53–64. http://dx.doi.org/10.1007/bf02304821.
Texto completoSunder, Shyam. "Management Control, Expectations, Common Knowledge, and Culture". Journal of Management Accounting Research 14, n.º 1 (1 de enero de 2002): 173–87. http://dx.doi.org/10.2308/jmar.2002.14.1.173.
Texto completoVan Zandt, Timothy y Martin Lettau. "ROBUSTNESS OF ADAPTIVE EXPECTATIONS AS AN EQUILIBRIUM SELECTION DEVICE". Macroeconomic Dynamics 7, n.º 1 (7 de enero de 2003): 89–118. http://dx.doi.org/10.1017/s1365100502010313.
Texto completoCho, In-Koo y Kenneth Kasa. "Gresham's Law of Model Averaging". American Economic Review 107, n.º 11 (1 de noviembre de 2017): 3589–616. http://dx.doi.org/10.1257/aer.20160665.
Texto completoXu, Xiaoli y Yibei Ling. "A study on the expectational model for tumor growth". International Journal of Bio-Medical Computing 22, n.º 2 (marzo de 1988): 135–41. http://dx.doi.org/10.1016/0020-7101(88)90049-9.
Texto completoKurozumi, Takushi y Willem Van Zandweghe. "TREND INFLATION AND EQUILIBRIUM STABILITY: FIRM-SPECIFIC VERSUS HOMOGENEOUS LABOR". Macroeconomic Dynamics 21, n.º 4 (8 de agosto de 2016): 947–81. http://dx.doi.org/10.1017/s1365100515000784.
Texto completoEvans, George W. y Seppo Honkapohja. "Expectational stability of stationary sunspot equilibria in a forward-looking linear model". Journal of Economic Dynamics and Control 28, n.º 1 (octubre de 2003): 171–81. http://dx.doi.org/10.1016/s0165-1889(02)00137-9.
Texto completoPfajfar, Damjan y Emiliano Santoro. "CREDIT MARKET DISTORTIONS, ASSET PRICES AND MONETARY POLICY". Macroeconomic Dynamics 18, n.º 3 (28 de septiembre de 2012): 631–50. http://dx.doi.org/10.1017/s1365100512000557.
Texto completoArifovic, Jasmina y James Bullard. "INTRODUCTION TO THE SPECIAL ISSUE: NEW APPROACHES TO LEARNING IN MACROECONOMIC MODELS". Macroeconomic Dynamics 5, n.º 02 (abril de 2001): 143–47. http://dx.doi.org/10.1017/s1365100501019010.
Texto completoTesis sobre el tema "Expectational Model"
Galbraith, J. W. "Modelling the formation of expectations". Thesis, University of Oxford, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.381848.
Texto completoKræmer, John Ph D. Massachusetts Institute of Technology. "An expectation model of referring expressions". Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62046.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (p. 297-205).
This thesis introduces EMRE, an expectation-based model of referring expressions. EMRE is proposed as a model of non-syntactic dependencies - in particular, discourse-level semantic dependencies that bridge sentence gaps. These include but are not limited to anaphora (references to noun phrases in previous sentences) and coherence predicates such as causality, temporal ordering and resemblance -- two domains that have typically been treated as entirely distinct aspects of language. EMRE is a computational-level model, and is agnostic about any particular algorithms, cognitive faculties, or neurological substrates that might be applied to the problem of semantic reference. Instead, it describes reference as a computational problem framed in terms of expectation and inference, and describes a solution to the problem based on rational top-down expectations about the likely targets of referring expressions, and on bottom-up feature-based matching that occurs when a referring expression is encountered. EMRE is used to derive novel empirical predictions about how people will construe particular discourse constructions involving NP anaphora and coherence predicates. These predictions are tested in controlled behavioral experiments, in which participants read and answer questions about short texts. The results of these experiments are shown to be consistent with a model of reference as an expectation-based computational structure with different underlying rules than those governing syntactic processing.
by John Kræmer.
Ph.D.
Morman, Karen. "Teacher Expectations of a Literacy Coaching Model". ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2415.
Texto completoZumpe, Martin Kai. "Stabilité macroéconomique, apprentissage et politique monétaire : une approche comparative : modélisation DSGE versus modélisation multi-agents". Thesis, Bordeaux 4, 2012. http://www.theses.fr/2012BOR40022/document.
Texto completoThis thesis analyses the role of learning in two different modelling frameworks. In the new canonicalmodel with adaptive learning, the most remarkable characteristics of the learning dynamics deal withthe capacity of monetary policy rules to guaranty convergence to the rational expectations equilibrium.The transmission mechanism of the monetary policy is based on the substitution effect associated to theconsumption channel. In the case of an agent-based model which relaxes some restrictive assumptionsof the new canonical model - but is endowed with a similar structure - aggregate variables evolve atsome distance from the rational expectations equilibrium. Monetary policy has a marginal impact onthe agregated variables via the wealth effect of the consumption channel. When agents learn accordingto an evolutionnary social learning process, the economy converges to regions of low economic activity.The introduction of a process where agents learn individually by using their mental models induces lessdepressive learning dynamics. These differences between the two modelling frameworks show that thegeneralisation of the results of the new canonical model is not easy to achieve
Creel, James Silas. "Intention is commitment with expectation". Texas A&M University, 2005. http://hdl.handle.net/1969.1/2313.
Texto completoQi, Yuan 1974. "Extending expectation propagation for graphical models". Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/30215.
Texto completoIncludes bibliographical references (p. 101-106).
Graphical models have been widely used in many applications, ranging from human behavior recognition to wireless signal detection. However, efficient inference and learning techniques for graphical models are needed to handle complex models, such as hybrid Bayesian networks. This thesis proposes extensions of expectation propagation, a powerful generalization of loopy belief propagation, to develop efficient Bayesian inference and learning algorithms for graphical models. The first two chapters of the thesis present inference algorithms for generative graphical models, and the next two propose learning algorithms for conditional graphical models. First, the thesis proposes a window-based EP smoothing algorithm for online estimation on hybrid dynamic Bayesian networks. For an application in wireless communications, window-based EP smoothing achieves estimation accuracy comparable to sequential Monte Carlo methods, but with less than one-tenth computational cost. Second, it develops a new method that combines tree-structured EP approximations with the junction tree for inference on loopy graphs. This new method saves computation and memory by propagating messages only locally to a subgraph when processing each edge in the entire graph. Using this local propagation scheme, this method is not only more accurate, but also faster than loopy belief propagation and structured variational methods. Third, it proposes predictive automatic relevance determination (ARD) to enhance classification accuracy in the presence of irrelevant features. ARD is a Bayesian technique for feature selection.
(cont.) The thesis discusses the overfitting problem associated with ARD, and proposes a method that optimizes the estimated predictive performance, instead of maximizing the model evidence. For a gene expression classification problem, predictive ARD outperforms previous methods, including traditional ARD as well as support vector machines combined with feature selection techniques. Finally, it presents Bayesian conditional random fields (BCRFs) for classifying interdependent and structured data, such as sequences, images or webs. BCRFs estimate the posterior distribution of model parameters and average prediction over this posterior to avoid overfitting. For the problems of frequently-asked-question labeling and of ink recognition, BCRFs achieve superior prediction accuracy over conditional random fields trained with maximum likelihood and maximum a posteriori criteria.
by Yuan Qi.
Ph.D.
Pollio, G. "Empirical tests of the rational expectations hypothesis". Thesis, City University London, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.351632.
Texto completoZhang, Xiaohua 1964. "Price expectations in perennial crop supply models". Thesis, The University of Arizona, 1991. http://hdl.handle.net/10150/291531.
Texto completoDavis, J. G. "A rational expectations model of the Federal Republic of Germany". Thesis, University of Liverpool, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.377979.
Texto completoElhouar, Mikael. "Essays on interest rate theory". Doctoral thesis, Handelshögskolan i Stockholm, Finansiell Ekonomi (FI), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-451.
Texto completoLibros sobre el tema "Expectational Model"
Dolado, Juan José. An expectational model of labour demand in Spanish industry. Madrid: Banco de España, Servicio de Estudios, 1985.
Buscar texto completoBranch, William A. Expectational stability in regime-switching rational expectations models. Kansas City [Mo.]: Research Division, Federal Reserve Bank of Kansas City, 2007.
Buscar texto completoKollintzas, Tryphon, ed. The Rational Expectations Equilibrium Inventory Model. New York, NY: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4684-6374-3.
Texto completoWestaway, Peter. Consistent expectations in the Treasury model. London: Treasury, 1986.
Buscar texto completoBlake, A. P. The Treasury model under rational expectations. London: University of London. Queen Mary College. Department of Economics, 1986.
Buscar texto completoPesaran, Hashem. Limited-dependent rational expectations models with future expectations. Cambridge: Department of Applied Economics, University of Cambridge, 1993.
Buscar texto completoFisher, Paul. Rational Expectations in Macroeconomic Models. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-015-8002-1.
Texto completoKowal, James A. Behavior models: Specifying users' expectations. Englewood Cliffs, New Jersey: Prentice-Hall, 1992.
Buscar texto completoKowal, James A. Behavior models: Specifying user's expectations. Englewood Cliffs, N.J: Prentice Hall, 1992.
Buscar texto completoRational expectations in macroeconomic models. Dordrecht: Kluwer Academic Publishers, 1992.
Buscar texto completoCapítulos de libros sobre el tema "Expectational Model"
Jiang, Di, Chen Zhang y Yuanfeng Song. "Expectation Maximization". En Probabilistic Topic Models, 53–62. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2431-8_4.
Texto completoOsborne, Martin J. y Ariel Rubinstein. "Equilibrium with prices and expectations". En Models in Microeconomic Theory, 187–202. 2a ed. Cambridge, UK: Open Book Publishers, 2023. http://dx.doi.org/10.11647/obp.0362.13.
Texto completoOsborne, Martin J. y Ariel Rubinstein. "Equilibrium with prices and expectations". En Models in Microeconomic Theory, 187–202. 2a ed. Cambridge, UK: Open Book Publishers, 2023. http://dx.doi.org/10.11647/obp.0361.13.
Texto completoDavis, Mark H. A. "Distributions and expectations". En Markov Models and Optimization, 81–133. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-4483-2_3.
Texto completoPauletto, Giorgio. "Rational Expectations Models". En Advances in Computational Economics, 93–137. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4757-2631-2_5.
Texto completoClements, Michael P. "Macroeconomic Uncertainty: Surveys Versus Models?" En Macroeconomic Survey Expectations, 123–43. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97223-7_7.
Texto completoClements, Michael P. "Behavioural Models of Expectations Formation". En Macroeconomic Survey Expectations, 145–72. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97223-7_8.
Texto completoFrydman, Roman y Michael D. Goldberg. "6. Opening Models of Asset Prices and Risk to Nonroutine Change". En Rethinking Expectations, editado por Roman Frydman y Edmund S. Phelps, 207–48. Princeton: Princeton University Press, 2013. http://dx.doi.org/10.1515/9781400846450.207.
Texto completoMitchell, Terence R. "Expectancy-Value Models in Organizational Psychology". En Expectations and Actions, 293–312. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003150879-16.
Texto completoHolden, K., D. A. Peel y J. L. Thompson. "Expectations in Econometric Models". En Expectations: Theory and Evidence, 143–62. London: Macmillan Education UK, 1985. http://dx.doi.org/10.1007/978-1-349-17862-9_6.
Texto completoActas de conferencias sobre el tema "Expectational Model"
Lu, Shu Quan, Shiyu Xie y Takao Ito. "Estimation of the Rigidity and Expectational Model". En 2009 Fifth International Joint Conference on INC, IMS and IDC. IEEE, 2009. http://dx.doi.org/10.1109/ncm.2009.148.
Texto completoYanagisawa, Hideyoshi y Natsu Mikami. "Effects of Expectation Uncertainty and Surprise on Quality Perception Factors of Expectation Effect". En ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34458.
Texto completoWells, Peter y J.-P. Skeete. "Circular Business Models as Instruments of Corporate Power". En New Business Models 2023. Maastricht University Press, 2023. http://dx.doi.org/10.26481/mup.2302.36.
Texto completoWan, Yi, Muhammad Zaheer, Adam White, Martha White y Richard S. Sutton. "Planning with Expectation Models". En Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/506.
Texto completoAbdulla, Farzanna Yashera y Jabil Mapjabil. "REVIEW OF THEORIES AND MODEL OF RESEARCH ON LIMINALITY IN TOURISM". En GLOBAL TOURISM CONFERENCE 2021. PENERBIT UMT, 2021. http://dx.doi.org/10.46754/gtc.2021.11.048.
Texto completoFink, Lauren K. "Computational models of temporal expectations". En Future Directions of Music Cognition. The Ohio State University Libraries, 2021. http://dx.doi.org/10.18061/fdmc.2021.0041.
Texto completo"SEMI-SUPERVISED LEARNING OF ALTERNATIVELY SPLICED EXONS USING EXPECTATION MAXIMIZATION TYPE APPROACHES". En International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003791802400245.
Texto completoMeng, Ming-Qiang y Yan-Kui Liu. "Fuzzy Expectation-Based Data Envelopment Analysis Model". En 2007 International Conference on Machine Learning and Cybernetics. IEEE, 2007. http://dx.doi.org/10.1109/icmlc.2007.4370341.
Texto completoChiang, Yu-Jui y Hsu-Feng Hsiao. "Expectation Model and Scheduling for Video Streaming". En 2018 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2018. http://dx.doi.org/10.1109/iscas.2018.8351571.
Texto completoChereshova, S. V. "Remuneration of Subjects of Parental Labour in Modern Russia: from Expectations to Reality". En XII Ural Demographic Forum “Paradigms and models of demographic development”. Institute of Economics of the Ural Branch of the Russian Academy of Sciences, 2021. http://dx.doi.org/10.17059/udf-2021-2-19.
Texto completoInformes sobre el tema "Expectational Model"
Oliveira, Lucas Gabriel Martins de. Which One Predicts Better?: Comparing Different GDP Nowcasting Methods Using Brazilian Data. Inter-American Development Bank, julio de 2023. http://dx.doi.org/10.18235/0005004.
Texto completoMolavi, Pooya, Alireza Tahbaz-Salehi y Andrea Vedolin. Model Complexity, Expectations, and Asset Prices. Cambridge, MA: National Bureau of Economic Research, enero de 2021. http://dx.doi.org/10.3386/w28408.
Texto completoRomero-Chamorro, José Vicente y Sara Naranjo-Saldarriaga. Weather Shocks and Inflation Expectations in Semi-Structural Models. Banco de la República Colombia, noviembre de 2022. http://dx.doi.org/10.32468/be.1218.
Texto completoHajdini, Ina, Edward S. Knotek, John Leer, Mathieu O. Pedemonte, Robert W. Rich y Raphael S. Schoenle. Low passthrough from inflation expectations to income growth expectations: why people dislike inflation. Federal Reserve Bank of Cleveland, marzo de 2023. http://dx.doi.org/10.26509/frbc-wp-202221r.
Texto completoHajdini, Ina. Mis-specified Forecasts and Myopia in an Estimated New Keynesian Model. Federal Reserve Bank of Cleveland, marzo de 2023. http://dx.doi.org/10.26509/frbc-wp-202203r.
Texto completoGaspar, Jess y Kenneth Judd. Solving Large Scale Rational Expectations Models. Cambridge, MA: National Bureau of Economic Research, febrero de 1997. http://dx.doi.org/10.3386/t0207.
Texto completoFarmer, Roger E. A., Tao Zha y Daniel Waggoner. Understanding Markov-Switching Rational Expectations Models. Cambridge, MA: National Bureau of Economic Research, febrero de 2009. http://dx.doi.org/10.3386/w14710.
Texto completoKoşar, Gizem y Cormac O'Dea. Expectations Data in Structural Microeconomic Models. Cambridge, MA: National Bureau of Economic Research, mayo de 2022. http://dx.doi.org/10.3386/w30094.
Texto completoBaldwin, Richard. The Core-Periphery Model with Forward-Looking Expectations. Cambridge, MA: National Bureau of Economic Research, febrero de 1999. http://dx.doi.org/10.3386/w6921.
Texto completoBeyer, Andreas, Roger E. Farmer, Jérôme Henry y Massimiliano Marcellino. Factor Analysis in a Model with Rational Expectations. Cambridge, MA: National Bureau of Economic Research, septiembre de 2007. http://dx.doi.org/10.3386/w13404.
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