Literatura académica sobre el tema "Principal component analysis"
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Artículos de revistas sobre el tema "Principal component analysis"
Barros, António S. y Douglas N. Rutledge. "Segmented principal component transform–principal component analysis". Chemometrics and Intelligent Laboratory Systems 78, n.º 1-2 (julio de 2005): 125–37. http://dx.doi.org/10.1016/j.chemolab.2005.01.003.
Texto completoGewers, Felipe L., Gustavo R. Ferreira, Henrique F. De Arruda, Filipi N. Silva, Cesar H. Comin, Diego R. Amancio y Luciano Da F. Costa. "Principal Component Analysis". ACM Computing Surveys 54, n.º 4 (mayo de 2021): 1–34. http://dx.doi.org/10.1145/3447755.
Texto completoRichards, Larry E. y I. T. Jolliffe. "Principal Component Analysis". Journal of Marketing Research 25, n.º 4 (noviembre de 1988): 410. http://dx.doi.org/10.2307/3172953.
Texto completoLever, Jake, Martin Krzywinski y Naomi Altman. "Principal component analysis". Nature Methods 14, n.º 7 (julio de 2017): 641–42. http://dx.doi.org/10.1038/nmeth.4346.
Texto completoTimmerman, Marieke E. "Principal Component Analysis". Journal of the American Statistical Association 98, n.º 464 (diciembre de 2003): 1082–83. http://dx.doi.org/10.1198/jasa.2003.s308.
Texto completoGoodall, Colin. "Principal Component Analysis". Technometrics 30, n.º 3 (agosto de 1988): 351–52. http://dx.doi.org/10.1080/00401706.1988.10488412.
Texto completoWold, Svante, Kim Esbensen y Paul Geladi. "Principal component analysis". Chemometrics and Intelligent Laboratory Systems 2, n.º 1-3 (agosto de 1987): 37–52. http://dx.doi.org/10.1016/0169-7439(87)80084-9.
Texto completoLaw, John y I. T. Jolliffe. "Principal Component Analysis." Statistician 36, n.º 4 (1987): 432. http://dx.doi.org/10.2307/2348864.
Texto completoHess, Aaron S. y John R. Hess. "Principal component analysis". Transfusion 58, n.º 7 (6 de mayo de 2018): 1580–82. http://dx.doi.org/10.1111/trf.14639.
Texto completoBro, Rasmus y Age K. Smilde. "Principal component analysis". Anal. Methods 6, n.º 9 (2014): 2812–31. http://dx.doi.org/10.1039/c3ay41907j.
Texto completoTesis sobre el tema "Principal component analysis"
Nunes, Madalena Baioa Paraíso. "Portfolio selection : a study using principal component analysis". Master's thesis, Instituto Superior de Economia e Gestão, 2017. http://hdl.handle.net/10400.5/14598.
Texto completoNesta tese aplicámos a análise de componentes principais ao mercado bolsista português usando os constituintes do índice PSI-20, de Julho de 2008 a Dezembro de 2016. Os sete primeiros componentes principais foram retidos, por se ter verificado que estes representavam as maiores fontes de risco deste mercado em específico. Assim, foram construídos sete portfólios principais e comparámo-los com outras estratégias de alocação. Foram construídos o portfólio 1/N (portfólio com investimento igual para cada um dos 26 ativos), o PPEqual (portfólio com igual investimento em cada um dos 7 principal portfólios) e o portfólio MV (portfólio que tem por base a teoria moderna de gestão de carteiras de Markowitz (1952)). Concluímos que estes dois últimos portfólios apresentavam os melhores resultados em termos de risco e retorno, sendo o portfólio PPEqual mais adequado a um investidor com maior grau de aversão ao risco e o portfólio MV mais adequado a um investidor que estaria disposto a arriscar mais em prol de maior retorno. No que diz respeito ao nível de risco, o PPEqual é o portfólio com melhores resultados e nenhum outro portfólio conseguiu apresentar valores semelhantes. Assim encontrámos um portfólio que é a ponderação de todos os portfólios principais por nós construídos e este era o portfólio mais eficiente em termos de risco.
In this thesis we apply principal component analysis to the Portuguese stock market using the constituents of the PSI-20 index from July 2008 to December 2016. The first seven principal components were retained, as we verified that these represented the major risk sources in this specific market. Seven principal portfolios were constructed and we compared them with other allocation strategies. The 1/N portfolio (with an equal investment in each of the 26 stocks), the PPEqual portfolio (with an equal investment in each of the 7 principal portfolios) and the MV portfolio (based on Markowitz's (1952) mean-variance strategy) were constructed. We concluded that these last two portfolios presented the best results in terms of return and risk, with PPEqual portfolio being more suitable for an investor with a greater degree of risk aversion and the MV portfolio more suitable for an investor willing to risk more in favour of higher returns. Regarding the level of risk, PPEqual is the portfolio with the best results and, so far, no other portfolio has presented similar values. Therefore, we found an equally-weighted portfolio among all the principal portfolios we built, which was the most risk efficient.
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Kpamegan, Neil Racheed. "Robust Principal Component Analysis". Thesis, American University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10784806.
Texto completoIn multivariate analysis, principal component analysis is a widely popular method which is used in many different fields. Though it has been extensively shown to work well when data follows multivariate normality, classical PCA suffers when data is heavy-tailed. Using PCA with the assumption that the data follows a stable distribution, we will show through simulations that a new method is better. We show the modified PCA can be used for heavy-tailed data and that we can more accurately estimate the correct number of components compared to classical PCA and more accurately identify the subspace spanned by the important components.
Akinduko, Ayodeji Akinwumi. "Multiscale principal component analysis". Thesis, University of Leicester, 2016. http://hdl.handle.net/2381/36616.
Texto completoDer, Ralf, Ulrich Steinmetz, Gerd Balzuweit y Gerrit Schüürmann. "Nonlinear principal component analysis". Universität Leipzig, 1998. https://ul.qucosa.de/id/qucosa%3A34520.
Texto completoSolat, Karo. "Generalized Principal Component Analysis". Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/83469.
Texto completoPh. D.
Fučík, Vojtěch. "Principal component analysis in Finance". Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-264205.
Texto completoWedlake, Ryan Stuart. "Robust principal component analysis biplots". Thesis, Link to the online version, 2008. http://hdl.handle.net/10019/929.
Texto completoBrennan, Victor L. "Principal component analysis with multiresolution". [Gainesville, Fla.] : University of Florida, 2001. http://etd.fcla.edu/etd/uf/2001/ank7079/brennan%5Fdissertation.pdf.
Texto completoTitle from first page of PDF file. Document formatted into pages; contains xi, 124 p.; also contains graphics. Vita. Includes bibliographical references (p. 120-123).
Cadima, Jorge Filipe Campinos Landerset. "Topics in descriptive Principal Component Analysis". Thesis, University of Kent, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314686.
Texto completoIsaac, Benjamin. "Principal component analysis based combustion models". Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209278.
Texto completoDoctorat en Sciences de l'ingénieur
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Libros sobre el tema "Principal component analysis"
Jolliffe, I. T. Principal component analysis. 2a ed. New York: Springer, 2010.
Buscar texto completoJolliffe, I. T. Principal Component Analysis. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8.
Texto completoPrincipal component analysis. New York: Springer-Verlag, 1986.
Buscar texto completoPrincipal component analysis. 2a ed. New York: Springer, 2002.
Buscar texto completoJuha, Karhunen y Oja Erkki, eds. Independent component analysis. New York: J. Wiley, 2001.
Buscar texto completoHyvarinen, Aapo. Independent component analysis. New York: J. Wiley, 2001.
Buscar texto completoVidal, René, Yi Ma y S. S. Sastry. Generalized Principal Component Analysis. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-0-387-87811-9.
Texto completoNaik, Ganesh R., ed. Advances in Principal Component Analysis. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6704-4.
Texto completoSanguansat, Parinya. Principal component analysis - multidisciplinary applications. Rijeka: InTech, 2012.
Buscar texto completoConstrained principal component analysis and related techniques. Boca Raton: CRC, Taylor & Francis Group, 2014.
Buscar texto completoCapítulos de libros sobre el tema "Principal component analysis"
Jolliffe, I. T. "Principal Component Analysis and Factor Analysis". En Principal Component Analysis, 115–28. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_7.
Texto completoJolliffe, I. T. "Introduction". En Principal Component Analysis, 1–7. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_1.
Texto completoJolliffe, I. T. "Outlier Detection, Influential Observations and Robust Estimation of Principal Components". En Principal Component Analysis, 173–98. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_10.
Texto completoJolliffe, I. T. "Principal Component Analysis for Special Types of Data". En Principal Component Analysis, 199–222. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_11.
Texto completoJolliffe, I. T. "Generalizations and Adaptations of Principal Component Analysis". En Principal Component Analysis, 223–34. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_12.
Texto completoJolliffe, I. T. "Mathematical and Statistical Properties of Population Principal Components". En Principal Component Analysis, 8–22. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_2.
Texto completoJolliffe, I. T. "Mathematical and Statistical Properties of Sample Principal Components". En Principal Component Analysis, 23–49. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_3.
Texto completoJolliffe, I. T. "Principal Components as a Small Number of Interpretable Variables: Some Examples". En Principal Component Analysis, 50–63. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_4.
Texto completoJolliffe, I. T. "Graphical Representation of Data Using Principal Components". En Principal Component Analysis, 64–91. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_5.
Texto completoJolliffe, I. T. "Choosing a Subset of Principal Components or Variables". En Principal Component Analysis, 92–114. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_6.
Texto completoActas de conferencias sobre el tema "Principal component analysis"
Tang, F. y H. Tao. "Binary Principal Component Analysis". En British Machine Vision Conference 2006. British Machine Vision Association, 2006. http://dx.doi.org/10.5244/c.20.39.
Texto completoSiirtola, Harri, Tanja Saily y Terttu Nevalainen. "Interactive Principal Component Analysis". En 2017 21st International Conference on Information Visualisation (IV). IEEE, 2017. http://dx.doi.org/10.1109/iv.2017.39.
Texto completoHsu, Charles y Harold Szu. "Sequential principal component analysis". En SPIE Defense, Security, and Sensing, editado por Harold Szu. SPIE, 2011. http://dx.doi.org/10.1117/12.887509.
Texto completoWang, Qianqian, Quanxue Gao, Xinbo Gao y Feiping Nie. "Angle Principal Component Analysis". En Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/409.
Texto completoPimentel-Alarcon, Daniel L., Aritra Biswas y Claudia R. Solis-Lemus. "Adversarial principal component analysis". En 2017 IEEE International Symposium on Information Theory (ISIT). IEEE, 2017. http://dx.doi.org/10.1109/isit.2017.8006952.
Texto completoSehgal, Shruti, Harpreet Singh, Mohit Agarwal, V. Bhasker y Shantanu. "Data analysis using principal component analysis". En 2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom). IEEE, 2014. http://dx.doi.org/10.1109/medcom.2014.7005973.
Texto completoWojnowicz, Michael, Dinh Nguyen, Li Li y Xuan Zhao. "Lazy Stochastic Principal Component Analysis". En 2017 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2017. http://dx.doi.org/10.1109/icdmw.2017.79.
Texto completoPei, Yan. "Linear Principal Component Discriminant Analysis". En 2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2015. http://dx.doi.org/10.1109/smc.2015.368.
Texto completoChowdhury, Ranak Roy, Muhammad Abdullah Adnan y Rajesh K. Gupta. "Real Time Principal Component Analysis". En 2019 IEEE 35th International Conference on Data Engineering (ICDE). IEEE, 2019. http://dx.doi.org/10.1109/icde.2019.00171.
Texto completo"CONSTRAINED GENERALISED PRINCIPAL COMPONENT ANALYSIS". En International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2006. http://dx.doi.org/10.5220/0001362102060212.
Texto completoInformes sobre el tema "Principal component analysis"
MARTIN, SHAWN B. Kernel Near Principal Component Analysis. Office of Scientific and Technical Information (OSTI), julio de 2002. http://dx.doi.org/10.2172/810934.
Texto completoHamilton, James y Jin Xi. Principal Component Analysis for Nonstationary Series. Cambridge, MA: National Bureau of Economic Research, enero de 2024. http://dx.doi.org/10.3386/w32068.
Texto completoAït-Sahalia, Yacine y Dacheng Xiu. Principal Component Analysis of High Frequency Data. Cambridge, MA: National Bureau of Economic Research, septiembre de 2015. http://dx.doi.org/10.3386/w21584.
Texto completoEick, Brian, Zachary Treece, Billie Spencer, Matthew Smith, Steven Sweeney, Quincy Alexander y Stuart Foltz. Miter gate gap detection using principal component analysis. Engineer Research and Development Center (U.S.), junio de 2018. http://dx.doi.org/10.21079/11681/27365.
Texto completoFederer, W. T., C. E. McCulloch y J. J. Miles-McDermott. Illustrative Examples of Principal Component Analysis Using SYSTAT/FACTOR. Fort Belvoir, VA: Defense Technical Information Center, mayo de 1987. http://dx.doi.org/10.21236/ada184920.
Texto completoFederer, W. T., C. E. McCulloch y N. J. Miles-McDermott. Illustrative Examples of Principal Component Analysis using BMDP/4M. Fort Belvoir, VA: Defense Technical Information Center, mayo de 1987. http://dx.doi.org/10.21236/ada185179.
Texto completoKrishnaiah, P. R. y S. Sarkar. Principal Component Analysis Under Correlated Multivariate Regression Equations Model. Fort Belvoir, VA: Defense Technical Information Center, abril de 1985. http://dx.doi.org/10.21236/ada160266.
Texto completoThompson, David C., Janine C. Bennett, Diana C. Roe y Philippe Pierre Pebay. Scalable multi-correlative statistics and principal component analysis with Titan. Office of Scientific and Technical Information (OSTI), febrero de 2009. http://dx.doi.org/10.2172/984172.
Texto completoFujikoshi, Y., P. R. Krishnaiah y J. Schmidhammer. Effect of Additional Variables in Principal Component Analysis, Discriminant Analysis and Canonical Correlation Analysis. Fort Belvoir, VA: Defense Technical Information Center, agosto de 1985. http://dx.doi.org/10.21236/ada162069.
Texto completoThompson, David, Ray W. Grout, Nathan D. Fabian y Janine Camille Bennett. Detecting Combustion and Flow Features In Situ Using Principal Component Analysis. Office of Scientific and Technical Information (OSTI), marzo de 2009. http://dx.doi.org/10.2172/1324759.
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