Relevant bibliographies by topics / Model selection

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Model selection'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Model selection"

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Lei, Y., and S. Y Zhang. "Comparison and selection of growth models using the Schnute model." Journal of Forest Science 52, No. 4 (2012): 188–96. http://dx.doi.org/10.17221/4501-jfs.

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Forestmodellers have long faced the problem of selecting an appropriate mathematical model to describe tree ontogenetic or size-shape empirical relationships for tree species. A common practice is to develop many models (or a model pool) that include different functional forms, and then to select the most appropriate one for a given data set. However, this process may impose subjective restrictions on the functional form. In this process, little attention is paid to the features (e.g. asymptote and inflection point rather than asymptote and nonasymptote) of different functional forms, and to t
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Solanki, Dr Ashvinkumar H. "Portfolio Selection Process through Markowitz Model." Indian Journal of Applied Research 4, no. 8 (2011): 356–58. http://dx.doi.org/10.15373/2249555x/august2014/90.

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Hoeting, Jennifer A., Richard A. Davis, Andrew A. Merton, and Sandra E. Thompson. "Model Selection For Geostatistical Models." Ecological Applications 16, no. 1 (2006): 87–98. http://dx.doi.org/10.1890/04-0576.

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Kapetanios, George. "Model Selection in Threshold Models." Journal of Time Series Analysis 22, no. 6 (2001): 733–54. http://dx.doi.org/10.1111/1467-9892.00251.

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Grace, James. "A 'Weight of Evidence' approach to evaluating structural equation models." One Ecosystem 5 (March 13, 2020): e50452. https://doi.org/10.3897/oneeco.5.e50452.

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It is possible that model selection has been the most researched and most discussed topic in the history of both statistics and structural equation modeling (SEM). The reason for this is because selecting one model for interpretive use from amongst many possible models is both essential and difficult. The published protocols and advice for model evaluation and selection in SEM studies are complex and difficult to integrate with current approaches used in biology. Opposition to the use of <i>p</i>-values and decision thresholds has been voiced by the statistics community, yet certain phases of
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Parr, William, H. Linhart, and W. Zucchini. "Model Selection." Journal of the American Statistical Association 84, no. 406 (1989): 620. http://dx.doi.org/10.2307/2289962.

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Blom, G., H. Linhart, and W. Zucchini. "Model Selection." Biometrics 45, no. 1 (1989): 340. http://dx.doi.org/10.2307/2532060.

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Brockett, Patrick L., H. Linhart, and W. Zucchini. "Model Selection." Journal of Marketing Research 25, no. 2 (1988): 214. http://dx.doi.org/10.2307/3172654.

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Viennet, G., F. Comte, and Y. Baraud. "model selection." Annals of Statistics 29, no. 3 (2001): 839–75. http://dx.doi.org/10.1214/aos/1009210692.

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Littell, Ramon C. "Model Selection." Technometrics 30, no. 1 (1988): 115–16. http://dx.doi.org/10.1080/00401706.1988.10488331.

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Dissertations / Theses on the topic "Model selection"

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Selén, Yngve. "Model selection /." Uppsala : Univ. : Dept. of Information Technology, Univ, 2004. http://www.it.uu.se/research/reports/lic/2004-003/.

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Selén, Yngve. "Model Selection." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-86308.

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Before using a parametric model one has to be sure that it offers a reasonable description of the system to be modeled. If a bad model structure is employed, the obtained model will also be bad, no matter how good is the parameter estimation method. There exist many possible ways of validating candidate models. This thesis focuses on one of the most common ways, i.e., the use of information criteria. First, some common information criteria are presented, and in the later chapters, various extentions and implementations are shown. An important extention, which is advocated in the thesis, is the
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Evers, Ludger. "Model fitting and model selection for 'mixture of experts' models." Thesis, University of Oxford, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445776.

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Billah, Baki 1965. "Model selection for time series forecasting models." Monash University, Dept. of Econometrics and Business Statistics, 2001. http://arrow.monash.edu.au/hdl/1959.1/8840.

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Yoshimura, Arihiro. "Essays on Semiparametric Model Selection and Model Averaging." Kyoto University, 2015. http://hdl.handle.net/2433/199059.

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PENG, SISI. "Evaluating Automatic Model Selection." Thesis, Uppsala universitet, Statistiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-154449.

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In this paper, we briefly describe the automatic model selection which is provided by Autometrics in the PcGive program. The modeler only needs to specify the initial model and the significance level at which to reduce the model. Then, the algorithm does the rest. The properties of Autometrics are discussed. We also explain its background concepts and try to see whether the model selected by the Autometrics can perform well. For a given data set, we use Autometrics to find a “new” model, and then compare the “new” model with a previously selected one by another modeler. It is an interesting is
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Bello, Bernardo. "PROCESS MANUFACTURING SELECTION MODEL." Thesis, KTH, Industriell produktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-218031.

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Aasberg, Pipirs Freddy, and Patrik Svensson. "Tenancy Model Selection Guidelines." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235716.

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Software as a Service (SaaS) is a subset of cloud services where a vendor provides software as a service to customers. The SaaS application is installed on the SaaS provider’s servers, and is often accessed via the web browser. In the context of SaaS, a customer is called tenant, which often is an organization that is accessing the SaaS application, but it could also be a single individual. A SaaS application can be classified into tenancy models. A tenancy model describes how a tenant’s data is mapped to the storage on the server-side of the SaaS application.By doing a research, the authors h
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Belitz, Christiane. "Model Selection in Generalised Structured Additive Regression Models." Diss., lmu, 2007. http://nbn-resolving.de/urn:nbn:de:bvb:19-78896.

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Sommer, Julia. "Regularized estimation and model selection in compartment models." Diss., Ludwig-Maximilians-Universität München, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-157673.

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Dynamic imaging series acquired in medical and biological research are often analyzed with the help of compartment models. Compartment models provide a parametric, nonlinear function of interpretable, kinetic parameters describing how some concentration of interest evolves over time. Aiming to estimate the kinetic parameters, this leads to a nonlinear regression problem. In many applications, the number of compartments needed in the model is not known from biological considerations but should be inferred from the data along with the kinetic parameters. As data from medical and biological exper
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Books on the topic "Model selection"

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missing], [name. Model selection. Institute of Mathematical Statistics, 2003.

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W, Zucchini, ed. Model selection. Wiley, 1986.

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Draper, Norman Richard. Model selection problems. University of Toronto, Dept. of Statistics, 1986.

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Burnham, Kenneth P., and David R. Anderson. Model Selection and Inference. Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2917-7.

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Picard, Jean, ed. Concentration Inequalities and Model Selection. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-48503-2.

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Burnham, Kenneth P., and David R. Anderson, eds. Model Selection and Multimodel Inference. Springer New York, 2004. http://dx.doi.org/10.1007/b97636.

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House, Christopher L. An sS model with adverse selection. National Bureau of Economic Research, 2000.

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Grasa, Antonio Aznar. Econometric Model Selection: A New Approach. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-017-1358-0.

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John F. Kennedy School of Government, ed. A "selection model" of political representation. John F. Kennedy School of Government, Harvard University, 2008.

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Jungeilges, Jochen A. The robustness of model selection rules. Lit, 1992.

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Book chapters on the topic "Model selection"

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Beyer, Dirk, Stefan Löwe, and Philipp Wendler. "Refinement Selection." In Model Checking Software. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23404-5_3.

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Castillo, Enrique, Angel Cobo, José Manuel Gutiérrez, and Rosa Eva Pruneda. "Model Selection." In Functional Networks with Applications. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5601-5_5.

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Raudys, Šarūnas. "Model Selection." In Statistical and Neural Classifiers. Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0359-2_6.

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Yandell, Brian S. "Model Selection." In Practical Data Analysis for Designed Experiments. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4899-3035-4_9.

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Bretthorst, G. Larry. "Model Selection." In Bayesian Spectrum Analysis and Parameter Estimation. Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4684-9399-3_5.

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Wang, Yuedong. "Model Selection." In Handbook of Computational Statistics. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21551-3_16.

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Blasco, Agustín. "Model Selection." In Bayesian Data Analysis for Animal Scientists. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54274-4_10.

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Fürnkranz, Johannes, Philip K. Chan, Susan Craw, et al. "Model Selection." In Encyclopedia of Machine Learning. Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_551.

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Yamanishi, Kenji. "Model Selection." In Learning with the Minimum Description Length Principle. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1790-7_3.

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Emmert-Streib, Frank, Salissou Moutari, and Matthias Dehmer. "Model Selection." In Elements of Data Science, Machine Learning, and Artificial Intelligence Using R. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-13339-8_12.

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Conference papers on the topic "Model selection"

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Berrezueta, Jose Maria, Santiago José Lituma Webster, Paúl Cárdenas-Delgado, and Priscila Cedillo. "Emotion-Based Interaction Mode Selection Model for University Students." In 2024 IEEE Eighth Ecuador Technical Chapters Meeting (ETCM). IEEE, 2024. http://dx.doi.org/10.1109/etcm63562.2024.10746154.

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Perugu, Sirisha, Jessica Holtorf, Vijay Dhar, and John Patrick Cleary. "Unique Model of Neonatal Palliative Care Delivery." In Selection of Abstracts From NCE 2015. American Academy of Pediatrics, 2017. http://dx.doi.org/10.1542/peds.140.1_meetingabstract.19.

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Duller, Christine. "Model selection for logistic regression models." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756152.

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Al-Refai, Mohammed, Walter Cazzola, and Sudipto Ghosh. "A Fuzzy Logic Based Approach for Model-Based Regression Test Selection." In 2017 ACM/IEEE 20th International Conference on Model-Driven Engineering Languages and Systems (MODELS). IEEE, 2017. http://dx.doi.org/10.1109/models.2017.17.

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Blanchard, Ashley, Bianca Calderon, Erin Cahill, et al. "Redesigning Primary Care Well Child Visits: A Group Model." In Selection of Abstracts From NCE 2016. American Academy of Pediatrics, 2018. http://dx.doi.org/10.1542/peds.141.1_meetingabstract.41.

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Adibhatla, S., and Z. Gastineau. "Tracking filter selection and control mode selection for model based control." In 30th Joint Propulsion Conference and Exhibit. American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-3204.

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Goldenberg, Alina, Janice Lucille Pelletier, and Sharon Jacob. "Pediatric Allergic Contact Dermatitis—quality Improvement via a Registry Model." In Selection of Abstracts From NCE 2016. American Academy of Pediatrics, 2018. http://dx.doi.org/10.1542/peds.141.1_meetingabstract.00.

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Welles, Mark, Bratic Julia, and Elise Seyferth. "An Educational Model to Change the Culture of Bullying in Schools." In Selection of Abstracts From NCE 2016. American Academy of Pediatrics, 2018. http://dx.doi.org/10.1542/peds.141.1_meetingabstract.246.

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Miller, Elissa, Meg Frizzola, Juliana Hayman, and Carly Levy. "A New Model to Improve Communication Training for Pediatric Icu Fellows." In Selection of Abstracts From NCE 2016. American Academy of Pediatrics, 2018. http://dx.doi.org/10.1542/peds.141.1_meetingabstract.373.

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Yan, Xiaoran. "Bayesian model selection of stochastic block models." In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2016. http://dx.doi.org/10.1109/asonam.2016.7752253.

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Reports on the topic "Model selection"

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Osipov, G. S. Fuzzy elective selection model. Редакция журнала «ОПиПМ», 2019. http://dx.doi.org/10.18411/oppm-2019-26-1.

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Moral, Rafael. Statistical Model Selection and Simplification. Instats Inc., 2024. http://dx.doi.org/10.61700/bg3im1fi4a4dm1478.

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This three-day workshop provides a comprehensive understanding of statistical model selection, comparison, simplification, and averaging using R software, essential for enhancing research methodologies and analytical skills. Participants will gain hands-on experience with advanced techniques such as nested model comparison, out-of-sample predictive performance, variable selection, model averaging, and Bayesian methods, culminating in improved data analysis proficiency and research outcomes.
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Madigan, David, and Adrian E. Raftery. Model Selection and Accounting for Model Uncertainty in Graphical Models Using OCCAM's Window. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada241408.

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Blume-Kohout, Robin J., and Travis L. Scholten. Characterizing Quantum Devices Using Model Selection. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1221861.

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Bai, Z. D., C. R. Rao, and Y. Wu. Model Selection with Data-Oriented Penalty. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada324872.

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Orozova, Daniela. Appropriate E-test System Selection Model. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2019. http://dx.doi.org/10.7546/crabs.2019.06.14.

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House, Christopher, and John Leahy. An sS Model with Adverse Selection. National Bureau of Economic Research, 2000. http://dx.doi.org/10.3386/w8030.

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Amit, Yali, and Donald Geman. A Computational Model for Visual Selection. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada344220.

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Wilhelm, Daniel, and Susanne M. Schennach. A simple parametric model selection test. The IFS, 2014. http://dx.doi.org/10.1920/wp.cem.2014.1014.

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Wilhelm, Daniel, and Susanne M. Schennach. A simple parametric model selection test. IFS, 2016. http://dx.doi.org/10.1920/wp.cem.2016.3016.

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