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Artykuły w czasopismach na temat "Non-Asymptotic and robust estimation"
Hirose, Kei, i Hiroki Masuda. "Robust Relative Error Estimation". Entropy 20, nr 9 (24.08.2018): 632. http://dx.doi.org/10.3390/e20090632.
Pełny tekst źródłaRudenko, O. G., О. О. Bessonov, N. М. Serdyuk, К. О. Olijnik i О. S. Romanyuk. "Robust object identification in the presence of non-Gaussian interference". Bionics of Intelligence 2, nr 93 (2.12.2019): 7–12. http://dx.doi.org/10.30837/bi.2019.2(93).02.
Pełny tekst źródłaEkundayo, Gbenga, i Ndubuisi Jeffery Jamani. "Estimation of Audit Delay Determinants: Do Outliers and Asymptotic Properties Matter?" European Journal of Business and Management Research 7, nr 5 (26.09.2022): 54–62. http://dx.doi.org/10.24018/ejbmr.2022.7.5.1604.
Pełny tekst źródłaCalderon, Sergio, i Daniel Ordoñez Callamad. "Additive Outliers in Open-Loop Threshold Autoregressive Models: A Simulation Study". Revista Colombiana de Estadística 45, nr 1 (1.01.2022): 1–39. http://dx.doi.org/10.15446/rce.v45n1.92965.
Pełny tekst źródłaLiu, Jie, Da-Yan Liu, Driss Boutat, Xuefeng Zhang i Ze-Hao Wu. "Innovative non-asymptotic and robust estimation method using auxiliary modulating dynamical systems". Automatica 152 (czerwiec 2023): 110953. http://dx.doi.org/10.1016/j.automatica.2023.110953.
Pełny tekst źródłaFiteni, Inmaculada. "ROBUST ESTIMATION OF STRUCTURAL BREAK POINTS". Econometric Theory 18, nr 2 (kwiecień 2002): 349–86. http://dx.doi.org/10.1017/s0266466602182065.
Pełny tekst źródłaRitov, Ya'acov. "Asymptotic results in robust quasi-bayesian estimation". Journal of Multivariate Analysis 23, nr 2 (grudzień 1987): 290–302. http://dx.doi.org/10.1016/0047-259x(87)90158-8.
Pełny tekst źródłaPoudyal, Chudamani. "ROBUST ESTIMATION OF LOSS MODELS FOR LOGNORMAL INSURANCE PAYMENT SEVERITY DATA". ASTIN Bulletin 51, nr 2 (5.03.2021): 475–507. http://dx.doi.org/10.1017/asb.2021.4.
Pełny tekst źródłaVermeulen, Karel, i Stijn Vansteelandt. "Data-Adaptive Bias-Reduced Doubly Robust Estimation". International Journal of Biostatistics 12, nr 1 (1.05.2016): 253–82. http://dx.doi.org/10.1515/ijb-2015-0029.
Pełny tekst źródłaChen, Haiqiang. "ROBUST ESTIMATION AND INFERENCE FOR THRESHOLD MODELS WITH INTEGRATED REGRESSORS". Econometric Theory 31, nr 4 (27.10.2014): 778–810. http://dx.doi.org/10.1017/s0266466614000553.
Pełny tekst źródłaRozprawy doktorskie na temat "Non-Asymptotic and robust estimation"
Sohrabi, Maryam. "On Robust Asymptotic Theory of Unstable AR(p) Processes with Infinite Variance". Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34280.
Pełny tekst źródłaDanilov, Mikhail. "Robust estimation of multivariate scatter in non-affine equivariant scenarios". Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/19462.
Pełny tekst źródłaTamburello, Philip Michael. "Iterative Memoryless Non-linear Estimators of Correlation for Complex-Valued Gaussian Processes that Exhibit Robustness to Impulsive Noise". Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/64785.
Pełny tekst źródłaPh. D.
Yan, Jiajia. "Statistical analysis on diffusion tensor estimation". Thesis, University of Wolverhampton, 2017. http://hdl.handle.net/2436/621860.
Pełny tekst źródłaFrontera, Pons Joana Maria. "Robust target detection for Hyperspectral Imaging". Thesis, Supélec, 2014. http://www.theses.fr/2014SUPL0024/document.
Pełny tekst źródłaHyperspectral imaging (HSI) extends from the fact that for any given material, the amount of emitted radiation varies with wavelength. HSI sensors measure the radiance of the materials within each pixel area at a very large number of contiguous spectral bands and provide image data containing both spatial and spectral information. Classical adaptive detection schemes assume that the background is zero-mean Gaussian or with known mean vector that can be exploited. However, when the mean vector is unknown, as it is the case for hyperspectral imaging, it has to be included in the detection process. We propose in this work an extension of classical detection methods when both covariance matrix and mean vector are unknown.However, the actual multivariate distribution of the background pixels may differ from the generally used Gaussian hypothesis. The class of elliptical distributions has already been popularized for background characterization in HSI. Although these non-Gaussian models have been exploited for background modeling and detection schemes, the parameters estimation (covariance matrix, mean vector) is usually performed using classical Gaussian-based estimators. We analyze here some robust estimation procedures (M-estimators of location and scale) more suitable when non-Gaussian distributions are assumed. Jointly used with M-estimators, these new detectors allow to enhance the target detection performance in non-Gaussian environment while keeping the same performance than the classical detectors in Gaussian environment. Therefore, they provide a unified framework for target detection and anomaly detection in HSI
Wang, Zhibo. "Estimations non-asymptotiques et robustes basées sur des fonctions modulatrices pour les systèmes d'ordre fractionnaire". Electronic Thesis or Diss., Bourges, INSA Centre Val de Loire, 2023. http://www.theses.fr/2023ISAB0003.
Pełny tekst źródłaThis thesis develops the modulating functions method for non-asymptotic and robust estimations for fractional-order nonlinear systems, fractional-order linear systems with accelerations as output, and fractional-order time-delay systems. The designed estimators are provided in terms of algebraic integral formulas, which ensure non-asymptotic convergence. As an essential feature of the designed estimation algorithms, noisy output measurements are only involved in integral terms, which endows the estimators with robustness against corrupting noises. First, for fractional-order nonlinear systems which are partially unknown, fractional derivative estimation of the pseudo-state is addressed via the modulating functions method. Thanks to the additive index law of fractional derivatives, the estimation is decomposed into the fractional derivatives estimation of the output and the fractional initial values estimation. Meanwhile, the unknown part is fitted via an innovative sliding window strategy. Second, for fractional-order linear systems with accelerations as output, fractional integral estimation of the acceleration is firstly considered for fractional-order mechanical vibration systems, where only noisy acceleration measurements are available. Based on the existing numerical approaches addressing the proper fractional integrals of accelerations, our attention is primarily restricted to estimating the unknown initial values using the modulating functions method. On this basis, the result is further generalized to more general fractional-order linear systems. In particular, the behaviour of fractional derivatives at zero is studied for absolutely continuous functions, which is quite different from that of integer order. Third, for fractional-order time-delay systems, pseudo-state estimation is studied by designing a fractional-order auxiliary modulating dynamical system, which provides a more general framework for generating the required modulating functions. With the introduction of the delay operator and the bicausal generalized change of coordinates, the pseudo-state estimation of the considered system can be reduced to that of the corresponding observer normal form. In contrast to the previous work, the presented scheme enables direct estimation for the pseudo-state rather than estimating the fractional derivatives of the output and a bunch of fractional initial values. In addition, the efficiency and robustness of the proposed estimators are verified by numerical simulations in this thesis. Finally, a summary of this work and an insight into future work were drawn
Beltaief, Slim. "Algorithmes optimaux de traitement de données pour des systèmes complexes d'information et télécommunication dans un environnement incertain". Thesis, Normandie, 2017. http://www.theses.fr/2017NORMR056/document.
Pełny tekst źródłaThis thesis is devoted to the problem of non parametric estimation for continuous-time regression models. We consider the problem of estimating an unknown periodoc function S. This estimation is based on observations generated by a stochastic process; these observations may be in continuous or discrete time. To this end, we construct a series of estimators by projection and thus we approximate the unknown function S by a finite Fourier series. In this thesis we consider the estimation problem in the adaptive setting, i.e. in situation when the regularity of the fonction S is unknown. In this way, we develop a new adaptive method based on the model selection procedure proposed by Konev and Pergamenshchikov (2012). Firstly, this procedure give us a family of estimators, then we choose the best possible one by minimizing a cost function. We give also an oracle inequality for the risk of our estimators and we give the minimax convergence rate
Liu, Jie. "State Estimation for Linear Singular and Nonlinear Dynamical Systems Based on Observable Canonical Forms". Electronic Thesis or Diss., Bourges, INSA Centre Val de Loire, 2024. http://www.theses.fr/2024ISAB0002.
Pełny tekst źródłaThis thesis aims, on the one hand, to design estimators for linear singular systems usingthemethod of modulation functions. On the other hand, it aims to develop observersfor a class of nonlinear dynamical systems using the method of canonical formsof observers. For singular systems, the designed estimators are presented in the formof algebraic integral equations, ensuring non-asymptotic convergence. An essentialcharacteristic of the designed estimation algorithms is that noisy measurements of theoutputs are only involved in integral terms, thereby imparting robustness to the estimatorsagainst perturbing noises. For nonlinear systems, the main design idea is totransform the proposed systems into a simplified form that accommodates existingobservers such as the high-gain observer and the sliding-mode observer. This simpleformis called auxiliary output depending observable canonical form.For the linear singular systems, we transform the considered system into a formsimilar to the Brunovsky’s observable canonical form with the injection of the inputs’and outputs’ derivatives. First, for linear singular systems with single input and singleoutput, the observability condition is proposed. The system’s input-output differentialequation is derived based on the Brunovsky’s observable canonical form. Algebraicformulas with a sliding integration window are obtained for the variables in differentsituations without knowing the system’s initial condition. Second, for linear singular systemswith multiple input and multiple output, an innovative nonasymptotic and robust estimation method based on the observable canonical form by means of a set of auxiliary modulating dynamical systems is introduced. The latter auxiliary systems are given by the controllable observable canonical with zero initial conditions. The proposed method is applied to estimate the states and the output’s derivatives for linear singular system in noisy environment. By introducing a set of auxiliary modulating dynamical systems which provides a more general framework for generating the requiredmodulating functions, algebraic integral formulas are obtained both for the state variables and the output’s derivatives. After giving the solutions of the required auxiliary systems, error analysis in discrete noisy case is addressed, where the provided noise error bound can be used to select design parameters.For the nonlinear dynamical systems, we propose a family of "ready to wear" nonlineardynamical systemswith multiple outputs that can be transformed into the outputauxiliarydepending observer normal forms which can support the well-known slidingmode observer. For this, by means of the so-called dynamics extension method anda set of changes of coordinates (basic algebraic integral computations), the nonlinearterms are canceled by auxiliary dynamics or replaced by nonlinear functions of themultiple outputs. It is worth mentioning that this procedure is finished in a comprehensible way without resort to the tools of differential geometry, which is user-friendly for those who are not familiar with the computations of Lie brackets. In addition, the efficiency and robustness of the proposed observers are verified by numerical simulations in this thesis. Second, a larger class of "ready to wear" nonlinear dynamicalsystems with multiple inputs and multiple outputs are provided to further extend anddevelop the systems proposed in the first case. In a similar way, by means of the corresponding auxiliary dynamics and a set of changes of coordinates, the provided systems are converted into targeted nonlinear observable canonical forms depending on both the multiple outputs and auxiliary variables. Naturally, this procedure is still completed without resort to geometrical tools. Finally, conclusions are outlined with some perspectives
Herrington, Richard S. "Simulating Statistical Power Curves with the Bootstrap and Robust Estimation". Thesis, University of North Texas, 2001. https://digital.library.unt.edu/ark:/67531/metadc2846/.
Pełny tekst źródłaVan, Deventer Petrus Jacobus Uys. "Outliers, influential observations and robust estimation in non-linear regression analysis and discriminant analysis". Doctoral thesis, University of Cape Town, 1993. http://hdl.handle.net/11427/4363.
Pełny tekst źródłaKsiążki na temat "Non-Asymptotic and robust estimation"
T, Rachev S., i Fabozzi Frank J, red. Robust and non-robust models in statistics. Hauppauge, NY: Nova Science Publishers, 2009.
Znajdź pełny tekst źródłaJurečková, Jana. Robust statistical procedures: Asymptotics and interrelations. New York: Wiley, 1996.
Znajdź pełny tekst źródłaClarke, Brenton R. Robustness Theory And Application: First edition. Redaktorzy J. Stuart Hunter i Joseph B. Kadane. Hoboken, New Jersey, USA: John Wiley & Sons, 2018.
Znajdź pełny tekst źródłaWheelock, David C. Robust non-parametric quantile estimation of efficiency and productivity change in U.S. commercial banking, 1985-2004. St. Louis, Mo.]: Federal Reserve Bank of St. Louis, 2006.
Znajdź pełny tekst źródłaCheng, Russell. Non-Standard Parametric Statistical Inference. Oxford, United Kingdom: Oxford University Press, 2017.
Znajdź pełny tekst źródłaJana Jurečková i Pranab Kumar Sen. Robust Statistical Procedures: Asymptotics and Interrelations. Wiley-Interscience, 1996.
Znajdź pełny tekst źródłaClarke, Brenton R. Robustness Theory and Application. Wiley & Sons, Limited, John, 2018.
Znajdź pełny tekst źródłaClarke, Brenton R. Robustness Theory and Application. Wiley & Sons, Incorporated, John, 2018.
Znajdź pełny tekst źródłaInverted Pendulum in Control Theory and Robotics: From Theory to New Innovations. Institution of Engineering & Technology, 2017.
Znajdź pełny tekst źródłaCzęści książek na temat "Non-Asymptotic and robust estimation"
Bednarski, Tadeusz. "Fréchet Differentiability and Robust Estimation". W Asymptotic Statistics, 49–58. Heidelberg: Physica-Verlag HD, 1994. http://dx.doi.org/10.1007/978-3-642-57984-4_4.
Pełny tekst źródłaKitsos, Christos P., i Christine H. Müller. "Robust Estimation of Non-linear Aspects". W Contributions to Statistics, 223–33. Heidelberg: Physica-Verlag HD, 1995. http://dx.doi.org/10.1007/978-3-662-12516-8_24.
Pełny tekst źródłaDe Brabanter, Jos, Kristiaan Pelckmans, Johan A. K. Suykens i Joos Vandewalle. "Robust Cross-Validation Score Function for Non-linear Function Estimation". W Artificial Neural Networks — ICANN 2002, 713–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-46084-5_116.
Pełny tekst źródłaSheng, Hu, YangQuan Chen i TianShuang Qiu. "Non-linear Transform Based Robust Adaptive Latency Change Estimation of Evoked Potentials". W Fractional Processes and Fractional-Order Signal Processing, 233–42. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2233-3_12.
Pełny tekst źródłaHu, Nan, Weimin Huang i Surendra Ranganath. "Robust Attentive Behavior Detection by Non-linear Head Pose Embedding and Estimation". W Computer Vision – ECCV 2006, 356–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11744078_28.
Pełny tekst źródłaKumar, Kunal, Prince Kumar i Susmita Kar. "A Non-Iterative Robust Scheme for Static State Estimation Based on S-Estimator Using Complex PMU Measurements". W Renewable Resources and Energy Management, 271–81. London: CRC Press, 2023. http://dx.doi.org/10.1201/9781003361312-31.
Pełny tekst źródłaNöll, Tobias, Johannes Köhler i Didier Stricker. "Robust and Accurate Non-parametric Estimation of Reflectance Using Basis Decomposition and Correction Functions". W Computer Vision – ECCV 2014, 376–91. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10605-2_25.
Pełny tekst źródłaRoensch, Birgit, i Wolfgang Stummer. "Robust Estimation by Means of Scaled Bregman Power Distances. Part I. Non-homogeneous Data". W Lecture Notes in Computer Science, 319–30. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26980-7_33.
Pełny tekst źródłaTavakkoli, Alireza, Mircea Nicolescu i George Bebis. "Automatic Robust Background Modeling Using Multivariate Non-parametric Kernel Density Estimation for Visual Surveillance". W Advances in Visual Computing, 363–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11595755_44.
Pełny tekst źródłaGolyanik, Vladislav. "Application of Point Set Registration and Monocular Non-Rigid 3D Reconstruction to Scene Flow Estimation". W Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds, 275–312. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-30567-3_10.
Pełny tekst źródłaStreszczenia konferencji na temat "Non-Asymptotic and robust estimation"
Xu, Yanwen, i Pingfeng Wang. "Sequential Sampling Based Reliability Analysis for High Dimensional Rare Events With Confidence Intervals". W ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22146.
Pełny tekst źródłaNugroho, Sebastian, Ahmad Taha i Junjian Qi. "Robust Dynamic State Estimation of Synchronous Machines with Asymptotic State Estimation Error Performance Guarantees". W 2020 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2020. http://dx.doi.org/10.1109/pesgm41954.2020.9281940.
Pełny tekst źródłaXu, Z. B., J. Y. Yao, Z. L. Dong i Y. Zheng. "Adaptive Robust Control for Hydraulic Actuators With Disturbance Estimation". W ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50133.
Pełny tekst źródłaAgamennoni, Gabriel, Stewart Worrall, James Ward i Eduardo Nebot. "Robust non-linear smoothing for vehicle state estimation". W 2013 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2013. http://dx.doi.org/10.1109/ivs.2013.6629464.
Pełny tekst źródłaFortunati, Stefano, Alexandre Renaux i Frederic Pascal. "Robust Semiparametric DOA Estimation in non-Gaussian Environment". W 2020 IEEE Radar Conference (RadarConf20). IEEE, 2020. http://dx.doi.org/10.1109/radarconf2043947.2020.9266451.
Pełny tekst źródłaSimpkins, Jonathan D., i Robert L. Stevenson. "Robust grid registration for non-blind PSF estimation". W IS&T/SPIE Electronic Imaging, redaktorzy Amir Said, Onur G. Guleryuz i Robert L. Stevenson. SPIE, 2012. http://dx.doi.org/10.1117/12.909887.
Pełny tekst źródłaTian, Kun, i Hai-hua Yu. "Robust non-fragile fault-tolerant H∞ control for time-delay uncertain linear systems". W 2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF). IEEE, 2015. http://dx.doi.org/10.1109/icedif.2015.7280214.
Pełny tekst źródłaZha, Jingqiang, Junmin Wang, Min Li, Xin Zhang i Xiao Yu. "Structured Robust Linear Parameter-Varying Vehicle Sideslip Angle Estimation". W ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9021.
Pełny tekst źródłaMohanty, Amit, i Bin Yao. "Indirect Adaptive Robust Control of Uncertain Systems With Unknown Asymmetric Input Deadband Using a Smooth Inverse". W ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2771.
Pełny tekst źródłaGrondin, Francois, i Francois Michaud. "Robust speech/non-speech discrimination based on pitch estimation for mobile robots". W 2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2016. http://dx.doi.org/10.1109/icra.2016.7487306.
Pełny tekst źródłaRaporty organizacyjne na temat "Non-Asymptotic and robust estimation"
Wheelock, David C., i Paul W. Wilson. Robust Non-parametric Quantile Estimation of Efficiency and Productivity Change in U.S. Commercial Banking, 1985-2004. Federal Reserve Bank of St. Louis, 2006. http://dx.doi.org/10.20955/wp.2006.041.
Pełny tekst źródłaHorowitz, Joel L. Non-asymptotic inference in instrumental variables estimation. The IFS, październik 2017. http://dx.doi.org/10.1920/wp.cem.2017.4617.
Pełny tekst źródłaHorowitz, Joel L. Non-asymptotic inference in instrumental variables estimation. The IFS, wrzesień 2018. http://dx.doi.org/10.1920/wp.cem.2018.5218.
Pełny tekst źródłaPowell, Andrew, i Matteo Bobba. Aid Effectiveness: Politics Matters. Inter-American Development Bank, styczeń 2007. http://dx.doi.org/10.18235/0010874.
Pełny tekst źródłaSchling, Maja, Nicolás Pazos, Leonardo Corral i Marisol Inurritegui. The Effects of Tenure Security on Women's Empowerment and Food Security: Evidence From a Land Regularization Program in Ecuador. Inter-American Development Bank, grudzień 2023. http://dx.doi.org/10.18235/0005355.
Pełny tekst źródłaBouezmarni, Taoufik, Mohamed Doukali i Abderrahim Taamouti. Copula-based estimation of health concentration curves with an application to COVID-19. CIRANO, 2022. http://dx.doi.org/10.54932/mtkj3339.
Pełny tekst źródłaZanoni, Wladimir, i Ailin He. Citizenship and the Economic Assimilation of Canadian Immigrants. Inter-American Development Bank, marzec 2021. http://dx.doi.org/10.18235/0003117.
Pełny tekst źródłaCattaneo, Matias D., Richard K. Crump i Weining Wang. Beta-Sorted Portfolios. Federal Reserve Bank of New York, lipiec 2023. http://dx.doi.org/10.59576/sr.1068.
Pełny tekst źródłaLee, W. S., Victor Alchanatis i Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, styczeń 2014. http://dx.doi.org/10.32747/2014.7598158.bard.
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