The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Definition and Comparison of Robust Nonlinear Data Smoothing Algorithms
Abstract
Nonlinear data smoothers provide a practical method of finding smooth traces for data confounded with possibly long-tailed or occasionally spikey noise. They are resistant to the effects of extreme observations that are not part of the local pattern, yet they are able to respond rapidly to well-supported patterns. This article defines a collection of nonlinear smoothers based upon running medians and presents methods for describing and comparing their performance. The characterizations of the smoothers presented here reveal some with excellent low-pass transfer characteristics, negligible Gibbs rebound, and resistance to the effects of non-Gaussian disturbances.
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Cites
Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables
W., J. W., Abramowitz, M., & Stegun, I. A. (1965) · Mathematics of Computation · doi:10.2307/2004114 · Cited by 18,663
Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables
Owen, D. B., Abramowitz, M., & Stegun, I. A. (1965) · Technometrics · doi:10.2307/1266136 · Cited by 16,138
David, F. N., & Tukey, J. W. (1977) · Biometrics · doi:10.2307/2529486 · Cited by 12,708
The Advanced Theory of Statistics.
Clarke, G. M., Kendall, M., & Stuart, A. (1978) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344782 · Cited by 6,658
Journal of The American Statistical Association
Fienberg, S. E. (2005) · Encyclopedia of Statistical Sciences · doi:10.1002/0471667196.ess1317 · Cited by 6,125
The Analysis of Time Series: An Introduction
Dickey, D. A., & Chatfield, C. (1991) · Technometrics · doi:10.2307/1268794 · Cited by 3,525
Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables.
H., C., Abramowitz, M., & Stegun, I. A. (1964) · Journal of the American Statistical Association · doi:10.2307/2282672 · Cited by 3,073
The Measurement of Power Spectra
Blackman, R. B., Tukey, J. W., & Teichmann, T. (1960) · Physics Today · doi:10.1063/1.3056826 · Cited by 1,843
Fourier Analysis of Time Series: An Introduction
Stoffer, D. S., & Bloomfield, P. (2000) · Journal of the American Statistical Association · doi:10.2307/2669794 · Cited by 1,690
Holder, R. L., Mosteller, F., & Tukey, J. W. (1979) · Applied Statistics · doi:10.2307/2346739 · Cited by 1,676
Cited by
A united states national reference for fetal growth
ALEXANDER, G., HIMES, J., KAUFMAN, R., MOR, J., & KOGAN, M. (1996) · Obstetrics & Gynecology · doi:10.1016/0029-7844(95)00386-x · Cited by 2,294
Birth weight in relation to morbidity and mortality among newborn infants
McIntire, D. D., Bloom, S. L., Casey, B. M., & Leveno, K. J. (1999) · New England Journal of Medicine · doi:10.1056/nejm199904223401603 · Cited by 1,258
Oken, E., Kleinman, K. P., Rich-Edwards, J., & Gillman, M. W. (2003) · BMC Pediatrics · doi:10.1186/1471-2431-3-6 · Cited by 940
Applications, Basics and Computing of Exploratory Data Analysis.
Ross, G. J. S., Vellenian, P. F., & Hoaglin, D. C. (1983) · Applied Statistics · doi:10.2307/2347963 · Cited by 835
Influenza and the Winter Increase in Mortality in the United States, 1959-1999
Reichert, T. A. (2004) · American Journal of Epidemiology · doi:10.1093/aje/kwh227 · Cited by 451
Metadata
- Authors
- Velleman, P. F.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1980-09
- Volume
- 75
- Issue
- 371
- Pages
- 609-615
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2088249878
- Cited by
- 262
- References
- 21
- FWCI
- 9.47
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
