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Relevant bibliographies by topics / The recursive diraction model

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Academic literature on the topic 'The recursive diraction model'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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Journal articles on the topic "The recursive diraction model"

1

Zeileis, Achim, Torsten Hothorn, and Kurt Hornik. "Model-Based Recursive Partitioning." Journal of Computational and Graphical Statistics 17, no. 2 (2008): 492–514. http://dx.doi.org/10.1198/106186008x319331.

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Chisholm, John. "Effective model theory vs. recursive model theory." Journal of Symbolic Logic 55, no. 3 (1990): 1168–91. http://dx.doi.org/10.2307/2274481.

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Recursive model theory is supposed to be the study of the effectiveness of constructions and theorems in model theory. This often involves getting “effective” versions of various classical model-theoretic notions. The traditional way of doing this is to restrict attention to recursive models, and recursive isomorphisms between them, etc. Thus for example the following definition appears in the literature (in [3] and [1]).Definition. Given a recursive model A and an n Є ω, a subset R ⊆ An is called intrinsically r.e. provided that for every recursive model B ≈ A, the isomorphic image in B of R

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3

Branch, William A., and George W. Evans. "A simple recursive forecasting model." Economics Letters 91, no. 2 (2006): 158–66. http://dx.doi.org/10.1016/j.econlet.2005.09.005.

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Ge, Zhiqiang, and Peikang Huang. "Nonlinear Recursive Minimum Model Error Estimation." Journal of Guidance, Control, and Dynamics 27, no. 1 (2004): 136–41. http://dx.doi.org/10.2514/1.9339.

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KOUCHNARENKO, O., and P. SCHNOEBELEN. "A model for recursive-parallel programs." Electronic Notes in Theoretical Computer Science 5 (April 2000): 1. http://dx.doi.org/10.1016/s1571-0661(05)01235-1.

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Kouchnarenko, Olga, and Ph Schnoebelen. "A model for recursive-parallel programs." Electronic Notes in Theoretical Computer Science 5 (1997): 30. http://dx.doi.org/10.1016/s1571-0661(05)82512-5.

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Rauschenberger, V., and H. M. Laun. "A recursive model for Rheotens tests." Journal of Rheology 41, no. 3 (1997): 719–37. http://dx.doi.org/10.1122/1.550880.

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Velotti, Lucia, and Jonathan B. Justice. "Operationalizing Giddens’s Recursive Model of Accountability." Public Performance & Management Review 40, no. 2 (2016): 310–35. http://dx.doi.org/10.1080/15309576.2016.1207549.

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EMARA-SHABAIK, Hosam E., Mohammed S. AHMED, and Khaled H. AL-AJMI. "Wiener-Hammerstein Model Identification-Recursive Algorithms." JSME International Journal Series C 45, no. 2 (2002): 606–13. http://dx.doi.org/10.1299/jsmec.45.606.

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Liu, Haoming, and Jie Zhang. "Donations in a recursive dynamic model." Canadian Journal of Economics/Revue canadienne d'économique 41, no. 2 (2008): 564–82. http://dx.doi.org/10.1111/j.1540-5982.2008.00475.x.

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Dissertations / Theses on the topic "The recursive diraction model"

1

Lu, Yao. "Propagation Modeling and Performance Evaluation in an Atrium Building." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177375.

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In this thesis electromagnetic wave propagation is investigated in an indoor environment. The indoor environment is a furnished office building with corridors, corners and rooms. Particularly, there is an atrium through the building in the center. For the study there were measurements available from real building in the 2.1 GHz frequency band. One objective is to design a propagation model that should be simple but reflect the trend of the propagation measurements. Furthermore, a system performance evaluation is carried out based on the implemented model. The proposed 3D model is a combination

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2

Zeileis, Achim, Torsten Hothorn, and Kurt Hornik. "Model-based recursive partitioning." Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, 2005. http://epub.wu.ac.at/54/1/document.pdf.

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Recursive partitioning is embedded into the general and well-established class of parametric models that can be fitted using M-type estimators (including maximum likelihood). An algorithm for model-based recursive partitioning is suggested for which the basic steps are: (1) fit a parametric model to a data set, (2) test for parameter instability over a set of partitioning variables, (3) if there is some overall parameter instability, split the model with respect to the variable associated with the highest instability, (4) repeat the procedure in each of the daughter nodes. The algorithm yields

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3

Kopf, Julia. "Model-based recursive partitioning meets item response theory." Diss., Ludwig-Maximilians-Universität München, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-164348.

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The aim of this thesis is to develop new statistical methods for the evaluation of assumptions that are crucial for reliably assessing group-differences in complex studies in the field of psychological and educational testing. The framework of item response theory (IRT) includes a variety of psychometric models for scaling latent traits such as the widely-used Rasch model. The Rasch model ensures objective measures and fair comparisons between groups of subjects. However, this important property holds only if the underlying assumptions are met. One essential assumption is the invariance proper

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Páez, Daýan. "Discrete, recursive supply chain model for solar panel manufacturing." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/58288.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2010.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 93).<br>A computer model to optimize global expansion of the production of solar panels is presented. The model is modular, extensible, and fast compared to existing specialized optimization software which use integer linear programming. The model inputs are (1) a tree of the assembly, or bill of materials (BOM), (2) a set of candidate locations where to build the product and any or all of its subcomponents, and (3) oth

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Viswanathan, Padma. "Implementing a Recursive Structure in a Relational Data Model." NSUWorks, 1994. http://nsuworks.nova.edu/gscis_etd/901.

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Li, Shujie. "A recursive Polya tree mixture model: computationally efficient Bayesian nonparametric modelling." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=121437.

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This thesis describes a flexible and computationally efficient Bayesian nonparametric modelling approach based on a recursive Polya tree mixture model. This approach is motivated by the need to capture the heterogeneity observed in many areas of biostatistics such as meta analysis of clinical trials, survival analysis and recurrent event data analysis. Let Y_{1},..,Y_{N} be mutually independent observations such that Y_i has distribution h(.|\theta_{i}). It is assumed that the parameters theta_{1},..., theta_{N} arise from an unknown distribution F and that the prior on F is a Polya tree dist

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Zeileis, Achim, Torsten Hothorn, and Kurt Hornik. "Evaluating Model-based Trees in Practice." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2006. http://epub.wu.ac.at/1484/1/document.pdf.

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A recently suggested algorithm for recursive partitioning of statistical models (Zeileis, Hothorn and Hornik, 2005), such as models estimated by maximum likelihood or least squares, is evaluated in practice. The general algorithm is applied to linear regression, logisitic regression and survival regression and applied to economical and medical regression problems. Furthermore, its performance with respect to prediction quality and model complexity is compared in a benchmark study with a large collection of other tree-based algorithms showing that the algorithm yields interpretable trees, compe

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Rusch, Thomas, and Achim Zeileis. "Gaining Insight with Recursive Partitioning of Generalized Linear Models." Taylor and Francis, 2013. http://dx.doi.org/10.1080/00949655.2012.658804.

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Recursive partitioning algorithms separate a feature space into a set of disjoint rectangles. Then, usually, a constant in every partition is fitted. While this is a simple and intuitive approach, it may still lack interpretability as to how a specific relationship between dependent and independent variables may look. Or it may be that a certain model is assumed or of interest and there is a number of candidate variables that may non-linearly give rise to different model parameter values. We present an approach that combines generalized linear models with recursive partitioning that offers en

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Rusch, Thomas, and Achim Zeileis. "Gaining Insight With Recursive Partitioning Of Generalized Linear Models." WU Vienna University of Economics and Business, 2011. http://epub.wu.ac.at/3143/6/paperEPUB.pdf.

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Recursive partitioning algorithms separate a feature space into a set of disjoint rectangles. Then, usually, a constant in every partition is fitted. While this is a simple and intuitive approach, it may still lack interpretability as to how a specific relationship between dependent and independent variables may look. Or it may be that a certain model is assumed or of interest and there is a number of candidate variables that may non-linearily give rise to different model parameter values. We present an approach that combines generalized linear models with recursive partitioning th

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Frühwirth-Schnatter, Sylvia. "Recursive Residuals and Model Diagnostics for Normal and Non-Normal State Space Models." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1994. http://epub.wu.ac.at/1540/1/document.pdf.

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Model diagnostics for normal and non-normal state space models is based on recursive residuals which are defined from the one-step ahead predictive distribution. Routine calculation of these residuals is discussed in detail. Various tools of diagnostics are suggested to check e.g. for wrong observation distributions and for autocorrelation. The paper also covers such topics as model diagnostics for discrete time series, model diagnostics for generalized linear models, and model discrimination via Bayes factors. (author's abstract)<br>Series: Forschungsberichte / Institut für Statistik

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Books on the topic "The recursive diraction model"

1

John, Elder. Compiler construction: A recursive descent model. Prentice Hall, 1994.

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2

Recursive identification based on the nonlinear Wiener model. Academia Upsaliensis, 1990.

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3

Birke, Hanna. Model-Based Recursive Partitioning with Adjustment for Measurement Error. Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-08505-6.

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4

Matulich, Scott C. A recursive age-structured model of Alaskan red king crab. Alaska Dept. of Fish and Game, Division of Commercial Fisheries, 1988.

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Matulich, Scott C. A recursive age-structured model of Alaskan red king crab. Alaska Dept. of Fish and Game, Division of Commercial Fisheries, 1988.

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6

Chen, S. Recursive maximum likelihood identification of a nonlinear output-affine model. University of Sheffield, Dept. of Control Engineering, 1987.

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7

Pesaran, Hashem. The use of recursive model selection strategies in forecasting stock returns. University of Cambridge, Department of Applied Economics, 1994.

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8

Binsbergen, Jules van. The term structure of interest rates in a DSGE model with recursive preferences. National Bureau of Economic Research, 2010.

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9

Bandyopadhyay, A. Initialization experiments over Indian region with a limited area model using recursive digital filters. Indian Institute of Tropical Meteorology, 2004.

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10

Karakus, Mustafa C. Implications of middle school behavior problems for high school graduation and employment outcomes of young adults: Estimation of a recursive model. National Bureau of Economic Research, 2010.

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Book chapters on the topic "The recursive diraction model"

1

Stolboushkin, Alexei P. "Towards Recursive Model Theory." In Logic Colloquium ’95. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-662-22108-2_18.

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2

Gabor, G., and Z. Györfi. "The Fine—McMillan Recursive Quantizer Model." In Recursive Source Coding. Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4613-8649-0_1.

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3

Teunissen, Peter J. G. "Batch and Recursive Model Validation." In Springer Handbook of Global Navigation Satellite Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-42928-1_24.

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4

Laarman, Alfons, Jaco van de Pol, and Michael Weber. "Parallel Recursive State Compression for Free." In Model Checking Software. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22306-8_4.

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Huang, Geng-Dian, Lin-Zan Cai, and Farn Wang. "LTL Model Checking for Recursive Programs." In Automated Technology for Verification and Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04761-9_28.

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Haindl, Michal. "Recursive Model-Based Colour Image Restoration." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-70659-3_64.

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Wu, William Z. "A Recursive Common Business Object System Model." In Business Object Design and Implementation III. Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0881-8_3.

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Landau, I. D., R. Lozano, and M. M’Saad. "Recursive Plant Model Identification in Open Loop." In Adaptive Control. Springer London, 1998. http://dx.doi.org/10.1007/978-0-85729-343-5_5.

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Landau, I. D., R. Lozano, and M. M’Saad. "Recursive Plant Model Identification in Closed Loop." In Adaptive Control. Springer London, 1998. http://dx.doi.org/10.1007/978-0-85729-343-5_9.

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Basu, Samik, K. Narayan Kumar, L. Robert Pokorny, and C. R. Ramakrishnan. "Resource-Constrained Model Checking of Recursive Programs." In Tools and Algorithms for the Construction and Analysis of Systems. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-46002-0_17.

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Conference papers on the topic "The recursive diraction model"

1

Dovžan, D., and I. Škrjanc. "Recursive Fuzzy Model Identification." In Advances in Computer Science and Engineering. ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.689-027.

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Vilar, Juan Miguel, and Enrique Vidal. "A recursive statistical translation model." In the ACL Workshop. Association for Computational Linguistics, 2005. http://dx.doi.org/10.3115/1654449.1654492.

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Wu, Fen, Andy Packard, and Kameshwar Poolla. "Recursive Methods for Model Validation." In 1993 American Control Conference. IEEE, 1993. http://dx.doi.org/10.23919/acc.1993.4792815.

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Yang, Chengliang, Anand Rangarajan, and Sanjay Ranka. "Global Model Interpretation Via Recursive Partitioning." In 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2018. http://dx.doi.org/10.1109/hpcc/smartcity/dss.2018.00256.

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Nikolaev, Konstantin, and Galina Grigoryeva. "Recursive Model for Multiplying Multidimensional Matrices." In 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). IEEE, 2019. http://dx.doi.org/10.1109/eiconrus.2019.8657307.

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Zhong-Hua Pang and Guo-Ping Liu. "Model-based recursive networked predictive control." In 2010 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2010. http://dx.doi.org/10.1109/icsmc.2010.5642322.

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Keyu Lu, Zhengmin Li, Zhaoxin Zhang, and Jiantao Shi. "DNS recursive server health evaluation model." In 2016 18TH Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2016. http://dx.doi.org/10.1109/apnoms.2016.7737281.

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Cooper, J., G. Poole, R. Wombell, and P. Wang. "Recursive Model-based Water-layer Demultiple." In 77th EAGE Conference and Exhibition 2015. EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201412687.

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Andresel, Medina, Julien Corman, Magdalena Ortiz, Juan L. Reutter, Ognjen Savkovic, and Mantas Simkus. "Stable Model Semantics for Recursive SHACL." In WWW '20: The Web Conference 2020. ACM, 2020. http://dx.doi.org/10.1145/3366423.3380229.

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Johnston, Douglas E., and Petar M. Djuric. "A Recursive Bayesian Model for Extreme Values." In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8682828.

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Reports on the topic "The recursive diraction model"

1

van Binsbergen, Jules, Jesús Fernández-Villaverde, Ralph S. J. Koijen, and Juan Rubio-Ramírez. The Term Structure of Interest Rates in a DSGE Model with Recursive Preferences. National Bureau of Economic Research, 2010. http://dx.doi.org/10.3386/w15890.

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Karakus, Mustafa, David Salkever, Eric Slade, Nicholas Ialongo, and Elizabeth Stuart. Implications of Middle School Behavior Problems for High School Graduation and Employment Outcomes of Young Adults: Estimation of a Recursive Model. National Bureau of Economic Research, 2010. http://dx.doi.org/10.3386/w16383.

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