12/15/2023 0 Comments Robust notion meaning![]() ![]() Zuo Y, Serfling R (2000) General notions of statistical depth function. Zuo Y (2003) Projection based depth functions and associated medians. In: Proceedings of the International Congress of Mathematicians, pp 523–531. Tukey JW (1975) Mathematics and the picturing of data. With discussion and a reply by the author. Stone CJ (1977) Consistent nonparametric regression. Rousseeuw PJ, Hubert M (1999) Regression depth (with discussion). Ramsay JO, Silverman BW (2005b) Functional data analysis, 2nd edn. Ramsay JO, Silverman BW (2005a) Applied functional data analysis. Ramsay JO, Silverman BW (2002) Applied functional data analysis. With discussion and a reply by the authors. Liu RY, Parelius JM, Singh K (1999) Multivariate analysis by data depth: descriptive statistics, graphics and inference. In their tree calculations, this notion of robust phase transitions was argued somehow to be more. In a recent paper(18) about phase transitions of spin models on general trees, Pemantle and Steif introduced a distinction between the notions of ordinary and ‘‘robust’’ phase transitions. Liu RY (1990) On a notion of data depth based on random simplices. KEY WORDS: Robust phase transitions Potts models. James GM, Hastie TJ (2001) Functional linear discriminant analysis for irregularly sampled curves. Hastie T, Tibshirani R, Friedman J (2001) The elements of statistical learning. Hastie T, Buja A, Tibshirani R (1995) Penalized discriminant analysis. Ghosh AK, Chaudhuri P (2005) On data depth and distribution-free discriminant analysis using separating surfaces. Test 8:255–317įraiman R, Muniz G (2001) Trimmed means for functional data. Springer, Heidelbergįraiman R, Meloche J (1999) Multivariate L-estimation. Springer, Heidelbergįishman GS (1996) Monte Carlo: concepts, algorithms and applications. Comput Stat Data Anal 44:161–173įerraty F, Vieu P (2006) Nonparametric modelling for functional data. Statist., Harvard Universityįerraty F, Vieu P (2003) Curves discrimination: a nonparametric functional approach. Springer, Heidelbergĭonoho DL (1982) Breakdown properties of multivariate location estimators. Comput Stat Data Anal 51:1063–1074ĭevroye L, Györfi L, Lugosi G (1996) A probabilistic theory of pattern recognition. Boletim da Sociedade Brasileira de Matematica 37:1–25Ĭuevas A, Febrero M, Fraiman R (2006) On the use of the bootstrap for estimating functions with functional data. J Theor Probab (in press)Ĭuesta-Albertos JA, Fraiman R, Ransford T (2006b) Random projections and goodness-of-fit tests in infinite-dimensional spaces. new and I find it remarkable how strong our intuitions are about when it does. PreprintĬuesta-Albertos JA, Fraiman R, Ransford T (2006a) A sharp form of the Cramer–Wold theorem. a notion of derivability which typically formalizes proofs by means of. Rather than put maximum exertion towards attaining the most ideal. ![]() IEEE Trans Inf Theory 51:2163–2172Ĭérou F, Guyader A (2005) Nearest neighbor classification in infinite dimension. Satisficing is a decision-making strategy that aims for a satisfactory or adequate result, rather than the optimal solution. Biau G, Bunea F, Wegkamp M (2005) Functional classification in Hilbert spaces. ![]()
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