Literatura académica sobre el tema "Density estimation"
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Artículos de revistas sobre el tema "Density estimation"
Sugiyama, Masashi, Takafumi Kanamori, Taiji Suzuki, Marthinus Christoffel du Plessis, Song Liu y Ichiro Takeuchi. "Density-Difference Estimation". Neural Computation 25, n.º 10 (octubre de 2013): 2734–75. http://dx.doi.org/10.1162/neco_a_00492.
Texto completoSasaki, Hiroaki, Yung-Kyun Noh, Gang Niu y Masashi Sugiyama. "Direct Density Derivative Estimation". Neural Computation 28, n.º 6 (junio de 2016): 1101–40. http://dx.doi.org/10.1162/neco_a_00835.
Texto completoYamane, Ikko, Hiroaki Sasaki y Masashi Sugiyama. "Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation". Neural Computation 28, n.º 7 (julio de 2016): 1388–410. http://dx.doi.org/10.1162/neco_a_00844.
Texto completoHovda, Sigve. "Properties of Transmetric Density Estimation". International Journal of Statistics and Probability 5, n.º 3 (13 de abril de 2016): 63. http://dx.doi.org/10.5539/ijsp.v5n3p63.
Texto completoLiu, Qing, David Pitt, Xibin Zhang y Xueyuan Wu. "A Bayesian Approach to Parameter Estimation for Kernel Density Estimation via Transformations". Annals of Actuarial Science 5, n.º 2 (18 de abril de 2011): 181–93. http://dx.doi.org/10.1017/s1748499511000030.
Texto completoBeaumont, Chris y B. W. Silverman. "Density Estimation." Journal of the Operational Research Society 37, n.º 11 (noviembre de 1986): 1102. http://dx.doi.org/10.2307/2582699.
Texto completoSheather, Simon J. "Density Estimation". Statistical Science 19, n.º 4 (noviembre de 2004): 588–97. http://dx.doi.org/10.1214/088342304000000297.
Texto completoYamada, Makoto y Masashi Sugiyama. "Direct Density-Ratio Estimation with Dimensionality Reduction via Hetero-Distributional Subspace Analysis". Proceedings of the AAAI Conference on Artificial Intelligence 25, n.º 1 (4 de agosto de 2011): 549–54. http://dx.doi.org/10.1609/aaai.v25i1.7905.
Texto completoLi, Rui y Youming Liu. "Wavelet Optimal Estimations for Density Functions under Severely Ill-Posed Noises". Abstract and Applied Analysis 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/260573.
Texto completoHovda, Sigve. "Transmetric Density Estimation". International Journal of Statistics and Probability 5, n.º 2 (10 de febrero de 2016): 35. http://dx.doi.org/10.5539/ijsp.v5n2p35.
Texto completoTesis sobre el tema "Density estimation"
Wang, Xiaoxia. "Manifold aligned density estimation". Thesis, University of Birmingham, 2010. http://etheses.bham.ac.uk//id/eprint/847/.
Texto completoRademeyer, Estian. "Bayesian kernel density estimation". Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/64692.
Texto completoDissertation (MSc)--University of Pretoria, 2017.
The financial assistance of the National Research Foundation (NRF) towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the authors and are not necessarily to be attributed to the NRF.
Statistics
MSc
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Stride, Christopher B. "Semi-parametric density estimation". Thesis, University of Warwick, 1995. http://wrap.warwick.ac.uk/109619/.
Texto completoRossiter, Jane E. "Epidemiological applications of density estimation". Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.291543.
Texto completoSung, Iyue. "Importance sampling kernel density estimation /". The Ohio State University, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=osu1486398528559777.
Texto completoKile, Håkon. "Bandwidth Selection in Kernel Density Estimation". Thesis, Norwegian University of Science and Technology, Department of Mathematical Sciences, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-10015.
Texto completoIn kernel density estimation, the most crucial step is to select a proper bandwidth (smoothing parameter). There are two conceptually different approaches to this problem: a subjective and an objective approach. In this report, we only consider the objective approach, which is based upon minimizing an error, defined by an error criterion. The most common objective bandwidth selection method is to minimize some squared error expression, but this method is not without its critics. This approach is said to not perform satisfactory in the tail(s) of the density, and to put too much weight on observations close to the mode(s) of the density. An approach which minimizes an absolute error expression, is thought to be without these drawbacks. We will provide a new explicit formula for the mean integrated absolute error. The optimal mean integrated absolute error bandwidth will be compared to the optimal mean integrated squared error bandwidth. We will argue that these two bandwidths are essentially equal. In addition, we study data-driven bandwidth selection, and we will propose a new data-driven bandwidth selector. Our new bandwidth selector has promising behavior with respect to the visual error criterion, especially in the cases of limited sample sizes.
Achilleos, Achilleas. "Deconvolution kernal density and regression estimation". Thesis, University of Bristol, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.544421.
Texto completoBuchman, Susan. "High-Dimensional Adaptive Basis Density Estimation". Research Showcase @ CMU, 2011. http://repository.cmu.edu/dissertations/169.
Texto completoLu, Shan. "Essays on volatility forecasting and density estimation". Thesis, University of Aberdeen, 2019. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=240161.
Texto completoChan, Kwokleung. "Bayesian learning in classification and density estimation /". Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC IP addresses, 2002. http://wwwlib.umi.com/cr/ucsd/fullcit?p3061619.
Texto completoLibros sobre el tema "Density estimation"
Stride, Christopher B. Semi-parametric density estimation. [s.l.]: typescript, 1995.
Buscar texto completoA. J. H. van Es. Aspects of nonparametric density estimation. Amsterdam, The Netherlands: Centrum voor Wiskunde en Informatica, 1991.
Buscar texto completoDevroye, Luc y Gábor Lugosi. Combinatorial Methods in Density Estimation. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0125-7.
Texto completoA course in density estimation. Boston: Birkhäuser, 1987.
Buscar texto completoLászló, Györfi, ed. Nonparametric density estimation: The L₁ view. New York: Wiley, 1985.
Buscar texto completoDevroye, Luc. Nonparametric density estimation: The L1 view. New York: Wiley, 1985.
Buscar texto completo1981-, Suzuki Taiji y Kanamori Takafumi 1971-, eds. Density ratio estimation in machine learning. Cambridge: Cambridge University Press, 2012.
Buscar texto completoSilverman, B. W. Density Estimation for Statistics and Data Analysis. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4899-3324-9.
Texto completoZinde-Walsh, Victoria. Kernel estimation when density does not exist. Montréal: Centre interuniversitaire de recherche en économie quantitative, 2005.
Buscar texto completoDensity estimation for statistics and data analysis. Boca Raton: Chapman & Hall/CRC, 1998.
Buscar texto completoCapítulos de libros sobre el tema "Density estimation"
Györfi, Lázió, Wolfgang Härdle, Pascal Sarda y Philippe Vieu. "Density Estimation". En Nonparametric Curve Estimation from Time Series, 53–79. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3686-3_4.
Texto completoWebb, Geoffrey I., Johannes Fürnkranz, Johannes Fürnkranz, Johannes Fürnkranz, Geoffrey Hinton, Claude Sammut, Joerg Sander et al. "Density Estimation". En Encyclopedia of Machine Learning, 270. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_210.
Texto completoKolassa, John E. "Density Estimation". En An Introduction to Nonparametric Statistics, 143–48. First edition. | Boca Raton : CRC Press, 2020. |: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9780429202759-8.
Texto completoSammut, Claude. "Density Estimation". En Encyclopedia of Machine Learning and Data Mining, 348–49. Boston, MA: Springer US, 2017. http://dx.doi.org/10.1007/978-1-4899-7687-1_210.
Texto completoLee, Myoung-jae. "Nonparametric Density Estimation". En Methods of Moments and Semiparametric Econometrics for Limited Dependent Variable Models, 123–42. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4757-2550-6_7.
Texto completoGu, Chong. "Probability Density Estimation". En Smoothing Spline ANOVA Models, 177–210. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4757-3683-0_6.
Texto completoHirukawa, Masayuki. "Univariate Density Estimation". En Asymmetric Kernel Smoothing, 17–39. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5466-2_2.
Texto completoHärdle, Wolfgang. "Kernel Density Estimation". En Springer Series in Statistics, 43–84. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-4432-5_2.
Texto completoSimonoff, Jeffrey S. "Multivariate Density Estimation". En Springer Series in Statistics, 96–133. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-4026-6_4.
Texto completoHärdle, Wolfgang, Axel Werwatz, Marlene Müller y Stefan Sperlich. "Nonparametric Density Estimation". En Springer Series in Statistics, 39–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17146-8_3.
Texto completoActas de conferencias sobre el tema "Density estimation"
Ram, Parikshit y Alexander G. Gray. "Density estimation trees". En the 17th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2020408.2020507.
Texto completoJooSeuk Kim y Clayton Scott. "Robust kernel density estimation". En ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/icassp.2008.4518376.
Texto completoMiao, Yun-Qian, Ahmed K. Farahat y Mohamed S. Kamel. "Discriminative Density-ratio Estimation". En Proceedings of the 2014 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2014. http://dx.doi.org/10.1137/1.9781611973440.95.
Texto completoSun, Ke y Stéphane Marchand-Maillet. "Information geometric density estimation". En BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING (MAXENT 2014). AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4905982.
Texto completoTing, Kai Ming, Takashi Washio, Jonathan R. Wells y Hang Zhang. "Isolation Kernel Density Estimation". En 2021 IEEE International Conference on Data Mining (ICDM). IEEE, 2021. http://dx.doi.org/10.1109/icdm51629.2021.00073.
Texto completoYilan, Mikail y Mehmet Kemal Ozdemir. "A simple approach to traffic density estimation by using Kernel Density Estimation". En 2015 23th Signal Processing and Communications Applications Conference (SIU). IEEE, 2015. http://dx.doi.org/10.1109/siu.2015.7130220.
Texto completoTakahashi, Hiroshi, Tomoharu Iwata, Yuki Yamanaka, Masanori Yamada y Satoshi Yagi. "Student-t Variational Autoencoder for Robust Density Estimation". En Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/374.
Texto completoSuga, Norisato, Kazuto Yano, Julian Webber, Yafei Hou, Toshihide Higashimori y Yoshinori Suzuki. "Estimation of Probability Density Function Using Multi-bandwidth Kernel Density Estimation for Throughput". En 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC). IEEE, 2020. http://dx.doi.org/10.1109/icaiic48513.2020.9065033.
Texto completoKrauthausen, Peter y Uwe D. Hanebeck. "Regularized non-parametric multivariate density and conditional density estimation". En 2010 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2010). IEEE, 2010. http://dx.doi.org/10.1109/mfi.2010.5604457.
Texto completoCharikar, Moses, Michael Kapralov, Navid Nouri y Paris Siminelakis. "Kernel Density Estimation through Density Constrained Near Neighbor Search". En 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2020. http://dx.doi.org/10.1109/focs46700.2020.00025.
Texto completoInformes sobre el tema "Density estimation"
Marchette, David J., Carey E. Priebe, George W. Rogers y Jeffrey L. Solka. Filtered Kernel Density Estimation. Fort Belvoir, VA: Defense Technical Information Center, octubre de 1994. http://dx.doi.org/10.21236/ada288293.
Texto completoMarchette, David J., Carey E. Priebe, George W. Rogers y Jefferey L. Solka. Filtered Kernel Density Estimation. Fort Belvoir, VA: Defense Technical Information Center, octubre de 1994. http://dx.doi.org/10.21236/ada290438.
Texto completoCollins, David H. Density estimation with trigonometric kernels. Office of Scientific and Technical Information (OSTI), febrero de 2016. http://dx.doi.org/10.2172/1237269.
Texto completoYu, Bin. Optimal Universal Coding and Density Estimation. Fort Belvoir, VA: Defense Technical Information Center, noviembre de 1994. http://dx.doi.org/10.21236/ada290694.
Texto completoRakhlin, Alexander, Dmitry Panchenko y Sayan Mukherjee. Risk Bounds for Mixture Density Estimation. Fort Belvoir, VA: Defense Technical Information Center, enero de 2004. http://dx.doi.org/10.21236/ada459846.
Texto completoSmith, Richard J. y Vitaliy Oryshchenko. Improved density and distribution function estimation. The IFS, julio de 2018. http://dx.doi.org/10.1920/wp.cem.2018.4718.
Texto completoPowell, James L., Fengshi Niu y Bryan S. Graham. Kernel density estimation for undirected dyadic data. The IFS, agosto de 2019. http://dx.doi.org/10.1920/wp.cem.2019.3919.
Texto completoChen, X. R., P. R. Krishnaiah y W. Q. Liang. Estimation of Multivariate Binary Density Using Orthonormal Functions. Fort Belvoir, VA: Defense Technical Information Center, diciembre de 1986. http://dx.doi.org/10.21236/ada186386.
Texto completoMellinger, David K. Detection, Classification, and Density Estimation of Marine Mammals. Fort Belvoir, VA: Defense Technical Information Center, octubre de 2012. http://dx.doi.org/10.21236/ada579344.
Texto completoMizera, Ivan y Roger Koenker. Shape constrained density estimation via penalized Rényi divergence. The IFS, septiembre de 2018. http://dx.doi.org/10.1920/wp.cem.2018.5418.
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