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Artykuły w czasopismach na temat "Principal component analysis"
Barros, António S., i Douglas N. Rutledge. "Segmented principal component transform–principal component analysis". Chemometrics and Intelligent Laboratory Systems 78, nr 1-2 (lipiec 2005): 125–37. http://dx.doi.org/10.1016/j.chemolab.2005.01.003.
Pełny tekst źródłaGewers, Felipe L., Gustavo R. Ferreira, Henrique F. De Arruda, Filipi N. Silva, Cesar H. Comin, Diego R. Amancio i Luciano Da F. Costa. "Principal Component Analysis". ACM Computing Surveys 54, nr 4 (maj 2021): 1–34. http://dx.doi.org/10.1145/3447755.
Pełny tekst źródłaRichards, Larry E., i I. T. Jolliffe. "Principal Component Analysis". Journal of Marketing Research 25, nr 4 (listopad 1988): 410. http://dx.doi.org/10.2307/3172953.
Pełny tekst źródłaLever, Jake, Martin Krzywinski i Naomi Altman. "Principal component analysis". Nature Methods 14, nr 7 (lipiec 2017): 641–42. http://dx.doi.org/10.1038/nmeth.4346.
Pełny tekst źródłaTimmerman, Marieke E. "Principal Component Analysis". Journal of the American Statistical Association 98, nr 464 (grudzień 2003): 1082–83. http://dx.doi.org/10.1198/jasa.2003.s308.
Pełny tekst źródłaGoodall, Colin. "Principal Component Analysis". Technometrics 30, nr 3 (sierpień 1988): 351–52. http://dx.doi.org/10.1080/00401706.1988.10488412.
Pełny tekst źródłaWold, Svante, Kim Esbensen i Paul Geladi. "Principal component analysis". Chemometrics and Intelligent Laboratory Systems 2, nr 1-3 (sierpień 1987): 37–52. http://dx.doi.org/10.1016/0169-7439(87)80084-9.
Pełny tekst źródłaLaw, John, i I. T. Jolliffe. "Principal Component Analysis." Statistician 36, nr 4 (1987): 432. http://dx.doi.org/10.2307/2348864.
Pełny tekst źródłaHess, Aaron S., i John R. Hess. "Principal component analysis". Transfusion 58, nr 7 (6.05.2018): 1580–82. http://dx.doi.org/10.1111/trf.14639.
Pełny tekst źródłaBro, Rasmus, i Age K. Smilde. "Principal component analysis". Anal. Methods 6, nr 9 (2014): 2812–31. http://dx.doi.org/10.1039/c3ay41907j.
Pełny tekst źródłaRozprawy doktorskie na temat "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.
Pełny tekst źródłaNesta 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.
Pełny tekst źródłaIn 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.
Pełny tekst źródłaDer, Ralf, Ulrich Steinmetz, Gerd Balzuweit i Gerrit Schüürmann. "Nonlinear principal component analysis". Universität Leipzig, 1998. https://ul.qucosa.de/id/qucosa%3A34520.
Pełny tekst źródłaSolat, Karo. "Generalized Principal Component Analysis". Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/83469.
Pełny tekst źródłaPh. D.
Fučík, Vojtěch. "Principal component analysis in Finance". Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-264205.
Pełny tekst źródłaWedlake, Ryan Stuart. "Robust principal component analysis biplots". Thesis, Link to the online version, 2008. http://hdl.handle.net/10019/929.
Pełny tekst źródłaBrennan, Victor L. "Principal component analysis with multiresolution". [Gainesville, Fla.] : University of Florida, 2001. http://etd.fcla.edu/etd/uf/2001/ank7079/brennan%5Fdissertation.pdf.
Pełny tekst źródłaTitle 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.
Pełny tekst źródłaIsaac, 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.
Pełny tekst źródłaDoctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
Książki na temat "Principal component analysis"
Jolliffe, I. T. Principal component analysis. Wyd. 2. New York: Springer, 2010.
Znajdź pełny tekst źródłaJolliffe, I. T. Principal Component Analysis. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8.
Pełny tekst źródłaPrincipal component analysis. New York: Springer-Verlag, 1986.
Znajdź pełny tekst źródłaPrincipal component analysis. Wyd. 2. New York: Springer, 2002.
Znajdź pełny tekst źródłaJuha, Karhunen, i Oja Erkki, red. Independent component analysis. New York: J. Wiley, 2001.
Znajdź pełny tekst źródłaHyvarinen, Aapo. Independent component analysis. New York: J. Wiley, 2001.
Znajdź pełny tekst źródłaVidal, René, Yi Ma i 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.
Pełny tekst źródłaNaik, Ganesh R., red. Advances in Principal Component Analysis. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6704-4.
Pełny tekst źródłaSanguansat, Parinya. Principal component analysis - multidisciplinary applications. Rijeka: InTech, 2012.
Znajdź pełny tekst źródłaConstrained principal component analysis and related techniques. Boca Raton: CRC, Taylor & Francis Group, 2014.
Znajdź pełny tekst źródłaCzęści książek na temat "Principal component analysis"
Jolliffe, I. T. "Principal Component Analysis and Factor Analysis". W Principal Component Analysis, 115–28. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_7.
Pełny tekst źródłaJolliffe, I. T. "Introduction". W Principal Component Analysis, 1–7. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_1.
Pełny tekst źródłaJolliffe, I. T. "Outlier Detection, Influential Observations and Robust Estimation of Principal Components". W Principal Component Analysis, 173–98. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_10.
Pełny tekst źródłaJolliffe, I. T. "Principal Component Analysis for Special Types of Data". W Principal Component Analysis, 199–222. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_11.
Pełny tekst źródłaJolliffe, I. T. "Generalizations and Adaptations of Principal Component Analysis". W Principal Component Analysis, 223–34. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_12.
Pełny tekst źródłaJolliffe, I. T. "Mathematical and Statistical Properties of Population Principal Components". W Principal Component Analysis, 8–22. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_2.
Pełny tekst źródłaJolliffe, I. T. "Mathematical and Statistical Properties of Sample Principal Components". W Principal Component Analysis, 23–49. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_3.
Pełny tekst źródłaJolliffe, I. T. "Principal Components as a Small Number of Interpretable Variables: Some Examples". W Principal Component Analysis, 50–63. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_4.
Pełny tekst źródłaJolliffe, I. T. "Graphical Representation of Data Using Principal Components". W Principal Component Analysis, 64–91. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_5.
Pełny tekst źródłaJolliffe, I. T. "Choosing a Subset of Principal Components or Variables". W Principal Component Analysis, 92–114. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4757-1904-8_6.
Pełny tekst źródłaStreszczenia konferencji na temat "Principal component analysis"
Tang, F., i H. Tao. "Binary Principal Component Analysis". W British Machine Vision Conference 2006. British Machine Vision Association, 2006. http://dx.doi.org/10.5244/c.20.39.
Pełny tekst źródłaSiirtola, Harri, Tanja Saily i Terttu Nevalainen. "Interactive Principal Component Analysis". W 2017 21st International Conference on Information Visualisation (IV). IEEE, 2017. http://dx.doi.org/10.1109/iv.2017.39.
Pełny tekst źródłaHsu, Charles, i Harold Szu. "Sequential principal component analysis". W SPIE Defense, Security, and Sensing, redaktor Harold Szu. SPIE, 2011. http://dx.doi.org/10.1117/12.887509.
Pełny tekst źródłaWang, Qianqian, Quanxue Gao, Xinbo Gao i Feiping Nie. "Angle Principal Component Analysis". W 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.
Pełny tekst źródłaPimentel-Alarcon, Daniel L., Aritra Biswas i Claudia R. Solis-Lemus. "Adversarial principal component analysis". W 2017 IEEE International Symposium on Information Theory (ISIT). IEEE, 2017. http://dx.doi.org/10.1109/isit.2017.8006952.
Pełny tekst źródłaSehgal, Shruti, Harpreet Singh, Mohit Agarwal, V. Bhasker i Shantanu. "Data analysis using principal component analysis". W 2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom). IEEE, 2014. http://dx.doi.org/10.1109/medcom.2014.7005973.
Pełny tekst źródłaWojnowicz, Michael, Dinh Nguyen, Li Li i Xuan Zhao. "Lazy Stochastic Principal Component Analysis". W 2017 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2017. http://dx.doi.org/10.1109/icdmw.2017.79.
Pełny tekst źródłaPei, Yan. "Linear Principal Component Discriminant Analysis". W 2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2015. http://dx.doi.org/10.1109/smc.2015.368.
Pełny tekst źródłaChowdhury, Ranak Roy, Muhammad Abdullah Adnan i Rajesh K. Gupta. "Real Time Principal Component Analysis". W 2019 IEEE 35th International Conference on Data Engineering (ICDE). IEEE, 2019. http://dx.doi.org/10.1109/icde.2019.00171.
Pełny tekst źródła"CONSTRAINED GENERALISED PRINCIPAL COMPONENT ANALYSIS". W International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2006. http://dx.doi.org/10.5220/0001362102060212.
Pełny tekst źródłaRaporty organizacyjne na temat "Principal component analysis"
MARTIN, SHAWN B. Kernel Near Principal Component Analysis. Office of Scientific and Technical Information (OSTI), lipiec 2002. http://dx.doi.org/10.2172/810934.
Pełny tekst źródłaHamilton, James, i Jin Xi. Principal Component Analysis for Nonstationary Series. Cambridge, MA: National Bureau of Economic Research, styczeń 2024. http://dx.doi.org/10.3386/w32068.
Pełny tekst źródłaAït-Sahalia, Yacine, i Dacheng Xiu. Principal Component Analysis of High Frequency Data. Cambridge, MA: National Bureau of Economic Research, wrzesień 2015. http://dx.doi.org/10.3386/w21584.
Pełny tekst źródłaEick, Brian, Zachary Treece, Billie Spencer, Matthew Smith, Steven Sweeney, Quincy Alexander i Stuart Foltz. Miter gate gap detection using principal component analysis. Engineer Research and Development Center (U.S.), czerwiec 2018. http://dx.doi.org/10.21079/11681/27365.
Pełny tekst źródłaFederer, W. T., C. E. McCulloch i J. J. Miles-McDermott. Illustrative Examples of Principal Component Analysis Using SYSTAT/FACTOR. Fort Belvoir, VA: Defense Technical Information Center, maj 1987. http://dx.doi.org/10.21236/ada184920.
Pełny tekst źródłaFederer, W. T., C. E. McCulloch i N. J. Miles-McDermott. Illustrative Examples of Principal Component Analysis using BMDP/4M. Fort Belvoir, VA: Defense Technical Information Center, maj 1987. http://dx.doi.org/10.21236/ada185179.
Pełny tekst źródłaKrishnaiah, P. R., i S. Sarkar. Principal Component Analysis Under Correlated Multivariate Regression Equations Model. Fort Belvoir, VA: Defense Technical Information Center, kwiecień 1985. http://dx.doi.org/10.21236/ada160266.
Pełny tekst źródłaThompson, David C., Janine C. Bennett, Diana C. Roe i Philippe Pierre Pebay. Scalable multi-correlative statistics and principal component analysis with Titan. Office of Scientific and Technical Information (OSTI), luty 2009. http://dx.doi.org/10.2172/984172.
Pełny tekst źródłaFujikoshi, Y., P. R. Krishnaiah i J. Schmidhammer. Effect of Additional Variables in Principal Component Analysis, Discriminant Analysis and Canonical Correlation Analysis. Fort Belvoir, VA: Defense Technical Information Center, sierpień 1985. http://dx.doi.org/10.21236/ada162069.
Pełny tekst źródłaThompson, David, Ray W. Grout, Nathan D. Fabian i Janine Camille Bennett. Detecting Combustion and Flow Features In Situ Using Principal Component Analysis. Office of Scientific and Technical Information (OSTI), marzec 2009. http://dx.doi.org/10.2172/1324759.
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