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Title: Smoothing and preservation of irregularities using local linear fitting (English)
Author: Gijbels, Irène
Language: English
Journal: Applications of Mathematics
ISSN: 0862-7940 (print)
ISSN: 1572-9109 (online)
Volume: 53
Issue: 3
Year: 2008
Pages: 177-194
Summary lang: English
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Category: math
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Summary: For nonparametric estimation of a smooth regression function, local linear fitting is a widely-used method. The goal of this paper is to briefly review how to use this method when the unknown curve possibly has some irregularities, such as jumps or peaks, at unknown locations. It is then explained how the same basic method can be used when estimating unsmooth probability densities and conditional variance functions. (English)
Keyword: density estimation
Keyword: irregularities
Keyword: jumps
Keyword: local linear fitting
Keyword: mean
Keyword: peaks
Keyword: preservation
Keyword: smoothing
Keyword: variance
MSC: 62G05
MSC: 62G07
MSC: 62G08
MSC: 62G20
idZBL: Zbl 1194.62044
idMR: MR2411123
DOI: 10.1007/s10492-008-0003-3
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Date available: 2010-07-20T12:15:05Z
Last updated: 2020-07-02
Stable URL: http://hdl.handle.net/10338.dmlcz/140314
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Reference: [1] Anscombe, F. J.: The transformation of Poisson, binomial and negative-binomial data.Biometrika 35 (1948), 246-254. Zbl 0032.03702, MR 0028556, 10.1093/biomet/35.3-4.246
Reference: [2] Antoch, J., Grégoire, G., Hušková, M.: Tests for continuity of regression function.J. Stat. Plann. Inference 137 (2007), 753-777. MR 2301714, 10.1016/j.jspi.2006.06.007
Reference: [3] Casas, I., Gijbels, I.: Estimation of smooth and non-smooth variance functions.Manuscript (2007).
Reference: [4] Desmet, L., Gijbels, I.: Peak preserving regression using local linear fitting.(2007), Submitted (2007).
Reference: [5] Fan, J., Gijbels, I.: Local Polynomial Modelling and its Applications.Chapman & Hall London (1996). Zbl 0873.62037, MR 1383587
Reference: [6] Fan, J., Yao, Q.: Efficient estimation of conditional variance functions in stochastic regression.Biometrika 85 (1998), 645-660. Zbl 0918.62065, MR 1665822, 10.1093/biomet/85.3.645
Reference: [7] Gao, J., Gijbels, I., Bellegem, S. Van: Nonparametric simultaneous testing for structural breaks.J. Econom. Special Issue on Specification Testing 143 (2008), 123-142. MR 2384436
Reference: [8] Gasser, T., Sroka, L., Jennen-Steinmetz, C.: Residual variance and residual pattern in nonlinear regression.Biometrika 73 (1986), 625-633. Zbl 0649.62035, MR 0897854, 10.1093/biomet/73.3.625
Reference: [9] Gijbels, I., Goderniaux, A.-C.: Bandwidth selection for change point estimation in nonparametric regression.Technometrics 46 (2004), 76-86. MR 2043389, 10.1198/004017004000000130
Reference: [10] Gijbels, I., Goderniaux, A.-C.: Bootstrap test for change-points in nonparametric regression.J. Nonparametric Stat. 16 (2004), 591-611. Zbl 1148.62304, MR 2073043, 10.1080/10485250310001626088
Reference: [11] Gijbels, I., Lambert, A., Qiu, P.: Edge-preserving image denoising and estimation of discontinuous surfaces.IEEE Trans. Pattern Anal. Mach. Intell. 28 (2006), 1075-1087. 10.1109/TPAMI.2006.140
Reference: [12] Gijbels, I., Lambert, A., Qiu, P.: Jump-preserving regression and smoothing using local linear fitting: A compromise.Ann. Inst. Stat. Math. 59 (2007), 235-272. MR 2394168, 10.1007/s10463-006-0045-9
Reference: [13] Grégoire, G., Hamrouni, Z.: Change-point estimation by local linear smoothing.J. Multivariate Anal. 83 (2002), 56-83. Zbl 1021.62026, MR 1934975, 10.1006/jmva.2001.2038
Reference: [14] Hall, P., Kay, J. W., Titterington, D. M.: Asymptotically optimal difference-based estimation of variance in nonparametric regression.Biometrika 77 (1990), 521-528. MR 1087842, 10.1093/biomet/77.3.521
Reference: [15] Hall, P., Titterington, D. M.: Edge preserving and peak-preserving smoothing.Technometrics 34 (1992), 429-440. MR 1190262, 10.1080/00401706.1992.10484954
Reference: [16] Hamrouni, Z.: Inférence statistique par lissage linéaire local pour une fonction de régression présentant des discontinuités.Doctoral Dissertation Université de Joseph Fourier Grenoble (1999).
Reference: [17] Jones, M. C., Foster, P.: A simple nonnegative boundary correction method for kernel density estimation.Stat. Sin. 6 (1996), 1005-1013. Zbl 0859.62037, MR 1422417
Reference: [18] Lambert, A.: Nonparametric estimation of discontinuous curves and surfaces.PhD. Dissertation Université catholique de Louvain Louvain-la-Neuve (2005).
Reference: [19] Marron, J. S., Ruppert, D.: Transformations to reduce boundary bias in kernel density estimation.J. R. Stat. Soc., Ser. B 56 (1994), 653-671. Zbl 0805.62046, MR 1293239
Reference: [20] McDonald, J. A., Owen, A. B.: Smoothing with split linear fits.Technometrics 28 (1986), 195-208. Zbl 0626.65010, MR 0853113, 10.1080/00401706.1986.10488127
Reference: [21] Müller, H.-G., Stadtmüller, U.: On variance function estimation with quadratic forms.J. Stat. Plann. Inference 35 (1993), 213-231. MR 1220417, 10.1016/0378-3758(93)90046-9
Reference: [22] Nadaraya, E. A.: On estimating regression.Theory Probab. Appl. 9 (1964), 141-142. Zbl 0136.40902
Reference: [23] Parzen, E.: On estimation of a probability density function and mode.Ann. Math. Stat. 33 (1962), 1065-1076. Zbl 0116.11302, MR 0143282, 10.1214/aoms/1177704472
Reference: [24] Qiu, P.: A jump-preserving curve fitting procedure based on local piecewise-linear kernel estimation.J. Nonparametric Stat. 15 (2003), 437-453. Zbl 1054.62047, MR 2017479, 10.1080/10485250310001595083
Reference: [25] Qiu, P.: Image Processing and Jump Regression Analysis.J. Wiley & Sons Hoboken (2005). Zbl 1070.68146, MR 2111430
Reference: [26] Rosenblatt, M.: Remarks on some nonparametric estimates of a density function.Ann. Inst. Math. Stat. 27 (1956), 832-837. Zbl 0073.14602, MR 0079873, 10.1214/aoms/1177728190
Reference: [27] Ruppert, D., Wand, M. P.: Multivariate locally weighted least squares regression.Ann. Stat. 22 (1994), 1346-1370. Zbl 0821.62020, MR 1311979, 10.1214/aos/1176325632
Reference: [28] Ruppert, D., Wand, M. P., Holst, U., Hössjer, O.: Local polynomial variance-function estimation.Technometrics 39 (1997), 262-273. MR 1462587, 10.1080/00401706.1997.10485117
Reference: [29] Schuster, E. F.: Incorporating support constraints into nonparametric estimators of densities.Commun. Stat., Theory Methods 14 (1985), 1123-1136. Zbl 0585.62070, MR 0797636, 10.1080/03610928508828965
Reference: [30] Watson, G. S.: Smooth regression analysis.Sankhya, Ser. A 26 (1964), 359-372. Zbl 0137.13002, MR 0185765
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