Literatura académica sobre el tema "Multi variate regression"
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Artículos de revistas sobre el tema "Multi variate regression"
Luo, Chongliang, Jin Liu, Dipak K. Dey y Kun Chen. "Canonical variate regression". Biostatistics 17, n.º 3 (9 de febrero de 2016): 468–83. http://dx.doi.org/10.1093/biostatistics/kxw001.
Texto completoChen, Zexun, Bo Wang y Alexander N. Gorban. "Multivariate Gaussian and Student-t process regression for multi-output prediction". Neural Computing and Applications 32, n.º 8 (31 de diciembre de 2019): 3005–28. http://dx.doi.org/10.1007/s00521-019-04687-8.
Texto completoÅström, Oskar, Henrik Hedlund y Alexandros Sopasakis. "Machine-Learning Approach to Non-Destructive Biomass and Relative Growth Rate Estimation in Aeroponic Cultivation". Agriculture 13, n.º 4 (30 de marzo de 2023): 801. http://dx.doi.org/10.3390/agriculture13040801.
Texto completode Laat, A. T. J., R. J. van der A y M. van Weele. "Tracing the second stage of Antarctic ozone hole recovery with a "big data" approach to multi-variate regressions". Atmospheric Chemistry and Physics Discussions 14, n.º 12 (14 de julio de 2014): 18591–640. http://dx.doi.org/10.5194/acpd-14-18591-2014.
Texto completoGholizadeh, Pouya y Behzad Esmaeili. "Developing a Multi-variate Logistic Regression Model to Analyze Accident Scenarios: Case of Electrical Contractors". International Journal of Environmental Research and Public Health 17, n.º 13 (6 de julio de 2020): 4852. http://dx.doi.org/10.3390/ijerph17134852.
Texto completoHongchao, Ma y Li Deren. "Enhancing group resolution of TM6 based on multi-variate regression model and semi-variogram function". Geo-spatial Information Science 4, n.º 1 (enero de 2001): 43–49. http://dx.doi.org/10.1007/bf02826636.
Texto completoMerz, B., H. Kreibich y U. Lall. "Multi-variate flood damage assessment: a tree-based data-mining approach". Natural Hazards and Earth System Sciences 13, n.º 1 (11 de enero de 2013): 53–64. http://dx.doi.org/10.5194/nhess-13-53-2013.
Texto completoBenson, Roger B. J. y Philip D. Mannion. "Multi-variate models are essential for understanding vertebrate diversification in deep time". Biology Letters 8, n.º 1 (22 de junio de 2011): 127–30. http://dx.doi.org/10.1098/rsbl.2011.0460.
Texto completoAmos, Kanyesiga Johnson y Bazinzi Natamba. "The Impact of Training and Development on Job Performance in Ugandan Banking Sector". Journal on Innovation and Sustainability. RISUS ISSN 2179-3565 6, n.º 2 (10 de agosto de 2015): 65. http://dx.doi.org/10.24212/2179-3565.2015v6i2p65-71.
Texto completoBarnes, R. J., M. S. Dhanoa y Susan J. Lister. "Standard Normal Variate Transformation and De-Trending of Near-Infrared Diffuse Reflectance Spectra". Applied Spectroscopy 43, n.º 5 (julio de 1989): 772–77. http://dx.doi.org/10.1366/0003702894202201.
Texto completoTesis sobre el tema "Multi variate regression"
Foxall, Robert John. "Likelihood analysis of the multi-layer perceptron and related latent variable models". Thesis, University of Newcastle Upon Tyne, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327211.
Texto completoWu, Hao. "Probabilistic Modeling of Multi-relational and Multivariate Discrete Data". Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/74959.
Texto completoPh. D.
Galindo-Prieto, Beatriz. "Novel variable influence on projection (VIP) methods in OPLS, O2PLS, and OnPLS models for single- and multi-block variable selection : VIPOPLS, VIPO2PLS, and MB-VIOP methods". Doctoral thesis, Umeå universitet, Kemiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-130579.
Texto completoSenapati, Swagatika. "Modelling of geotechnical structures using multi-variate adaptive regression spline (MARS) and genetic programming (GP)". Thesis, 2013. http://ethesis.nitrkl.ac.in/5345/1/211CE1017.pdf.
Texto completoSteyn, Hendrik Stefanus. "The use of effect sizes in credit rating models". Diss., 2014. http://hdl.handle.net/10500/18790.
Texto completoStatistics
M. Sc. (Statistics)
Libros sobre el tema "Multi variate regression"
Halperin, Sandra y Oliver Heath. 17. A Guide to Multivariate Analysis. Oxford University Press, 2017. http://dx.doi.org/10.1093/hepl/9780198702740.003.0017.
Texto completoCapítulos de libros sobre el tema "Multi variate regression"
Bonamente, Massimiliano. "Multi-variable Regression". En Statistics and Analysis of Scientific Data, 247–61. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0365-6_13.
Texto completoBonamente, Massimiliano. "Multi-Variable Regression". En Statistics and Analysis of Scientific Data, 165–75. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-6572-4_9.
Texto completoChen, Wan-Ping, Ying Nian Wu y Ray-Bin Chen. "Bayesian Variable Selection for Multi-response Linear Regression". En Technologies and Applications of Artificial Intelligence, 74–88. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-13987-6_8.
Texto completoYang, Kaifeng y Michael Affenzeller. "Surrogate-assisted Multi-objective Optimization via Genetic Programming Based Symbolic Regression". En Lecture Notes in Computer Science, 176–90. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27250-9_13.
Texto completoOlaru, Gabriel, Alexander Robitzsch, Andrea Hildebrandt y Ulrich Schroeders. "An Illustration of Local Structural Equation Modeling for Longitudinal Data: Examining Differences in Competence Development in Secondary Schools". En Methodology of Educational Measurement and Assessment, 153–76. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27007-9_7.
Texto completoXu, You. "A Gradient-Based ELM Algorithm in Regressing Multi-variable Functions". En Advances in Neural Networks - ISNN 2006, 653–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11759966_96.
Texto completoSeo, In-Yong, Bok-Nam Ha y Min-Ho Park. "Multi-response Variable Optimization in Sensor Drift Monitoring System Using Support Vector Regression". En Intelligent Information and Database Systems, 21–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20042-7_3.
Texto completoBarba, Lida, Nibaldo Rodríguez, Ana Congacha y Lady Espinoza. "Multi-resolution SVD, Linear Regression, and Extreme Learning Machine for Traffic Accidents Forecasting with Climatic Variable". En Lecture Notes in Networks and Systems, 501–17. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82196-8_37.
Texto completoDo Luu, Duc y Luu Minh Hai. "Multi-variable Regressive Models for Diagnostics of the Unbalances on Rapid Rotor in Shop Dynamic Balance". En Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020), 267–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69610-8_37.
Texto completoOda, Ryoya. "Kick-One-Out-Based Variable Selection Method Using Ridge-Type $$C_{p}$$ Criterion in High-Dimensional Multi-response Linear Regression Models". En Intelligent Decision Technologies, 193–202. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2969-6_17.
Texto completoActas de conferencias sobre el tema "Multi variate regression"
Uddin, Rokan, Fahim Irfan Alam, Avisheak Das y Sadia Sharmin. "Multi-Variate Regression Analysis for Stock Market price prediction using Stacked LSTM". En 2022 International Conference on Innovations in Science, Engineering and Technology (ICISET). IEEE, 2022. http://dx.doi.org/10.1109/iciset54810.2022.9775911.
Texto completoSastry, Rambhatla G. y Sumedha Chahr. "MULTI-VARIATE REGRESSION ANALYSIS OF GEO-ELECTRIC IMAGING AND GEOTECHNICAL SITE INVESTIGATION TEST RESULTS - A CASE STUDY". En Symposium on the Application of Geophysics to Engineering and Environmental Problems 2015. Society of Exploration Geophysicists and Environment and Engineering Geophysical Society, 2016. http://dx.doi.org/10.4133/sageep.29-033.
Texto completoSharma, Akash y Brandon Guttery. "Multivariate Modeling of Terminal Decline Rate in Parent and Child Wells in Unconventional Reservoirs". En SPE Western Regional Meeting. SPE, 2021. http://dx.doi.org/10.2118/200876-ms.
Texto completoRoy Chowdhury, Joydeb, Aditya Chatterjee, Saikat Basu, Sayan Goswami, Suvradipta Saha, Surajit Poddar y Anup Bhattacharjee. "Design Methodology of Solar Powered Load Controller Using Sensor Assisted Remote Battery State of Charge Estimator". En ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-37008.
Texto completoSlaveski, Trajko y Darko Lazarov. "How Do Institutions Determine Economic Growth? Evidеnce from Central and Eastern Europe before and during Global Economic Crisis". En International Conference on Eurasian Economies. Eurasian Economists Association, 2014. http://dx.doi.org/10.36880/c05.01040.
Texto completoOliveira, Emerson V., David H. do Santos y Luiz M. G. Goncalves. "Auto-regressive Multi-variable Auto-encoder". En Anais Estendidos da Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/sibgrapi.est.2022.23279.
Texto completoOmion, Osemanre Ossy, Chioma Maduewesi y Emeke Chukwu. "A Novel Approach to Predicting Combustion Emission Using Ambient Air Quality Parameters in Onshore Eastern Nigeria". En SPE Nigeria Annual International Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/207139-ms.
Texto completoXu, Hongyi, Ching-Hung Chuang y Ren-Jye Yang. "Mixed-Variable Metamodeling Methods for Designing Multi-Material Structures". En ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59176.
Texto completoZhang, Haocheng. "The Establishment of Multi-variable Linear Regression in Steam Sales". En 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/aebmr.k.220307.137.
Texto completoAbele, Sebastian y Michael Weyrich. "Supporting the regression test of multi-variant systems in distributed production scenarios". En 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, 2016. http://dx.doi.org/10.1109/etfa.2016.7733652.
Texto completoInformes sobre el tema "Multi variate regression"
Baete, Christophe y Keith Parker. PR405-213601-R04 Validation of Digital Twins for Monitoring, Optimization, and Compliance of CP Systems. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), marzo de 2023. http://dx.doi.org/10.55274/r0012254.
Texto completoAlexander, Serena E., Mariela Alfonzo y Kevin Lee. Safeguarding Equity in Off-Site Vehicle Miles Traveled (VMT) Mitigation in California. Mineta Transportation Institute, noviembre de 2021. http://dx.doi.org/10.31979/mti.2021.2027.
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