LOWESS: This durable set of base routines, written in Fortran in the late 1970s, are widely used. They smooth just as a function of one predictor for data with normal errors or for data with long-tailed symmetric errors (robust fitting). Statistics for inference are not computed. S-Plus, R, Systat, XploRE, Gauss, and SAS have interfaces to LOWESS. LOWESS base software from netlib. SAS macro from Michael Friendly. LOWESS was introduced in Visual and Computational Considerations in Smoothing Scatterplots by Locally Weighted Fitting. W. S. Cleveland. In Computer Science and Statistics: Eleventh Annual Symposium on the Interface, pages 96-100. Institute of Statistics, North Carolina State University, Raleigh, North Carolina, 1978. Robust Locally Weighted Fitting and Smoothing Scatterplots. W. S. Cleveland. Journal of the American Statistical Association, 74:829-836, 1979. Computational methods were developed in LOWESS: A Program for Smoothing Scatterplots by Robust Locally Weighted Fitting. W. S. Cleveland. The American Statistician, 35:54, 1981. and implemented in the above base software.

References in zbMATH (referenced in 15 articles )

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  1. Jamshidi, Arta A.; Powell, Warren B.: A recursive local polynomial approximation method using Dirichlet clouds and radial basis functions (2016)
  2. Gill, Jeff: Bayesian methods. A social and behavioral sciences approach (2015)
  3. Lindqvist, Bo Henry; Kvaløy, Jan Terje; Aaserud, Stein: Residual plots to reveal the functional form for covariates in parametric accelerated failure time models (2015)
  4. Nadarajah, Saralees; Teimouri, Mahdi; Shih, Shou Hsing: Characterizations of the Weibull and uniform distributions using record values (2014)
  5. Withers, Christopher S.; Nadarajah, Saralees: Correlation is first order independent of transformation (2013)
  6. Knapp, Bettina: RNA interference data: from a statistical analysis to network inference (2012)
  7. Withers, Christopher S.; Nadarajah, Saralees: Unbiased estimates for a lognormal regression problem and a nonparametric alternative (2012)
  8. Lemaire, Pierre: Extensions of logical analysis of data for growth hormone deficiency diagnoses (2011) ioport
  9. Morey, Richard D.: A Bayesian hierarchical model for the measurement of working memory capacity (2011)
  10. Nadarajah, Saralees: The exponentiated exponential distribution: a survey (2011)
  11. Withers, Christopher S.; Nadarajah, Saralees: Bias-reduced estimates for skewness, kurtosis, $L$-skewness and $L$-kurtosis (2011)
  12. Behr, Andreas: Quantile regression for robust bank efficiency score estimation (2010)
  13. Dai, Jing; Sperlich, S.: Simple and effective boundary correction for kernel densities and regression with an application to the world income and Engel curve estimation (2010)
  14. Scharpf, Robert B.; Iacobuzio-Donahue, Christine A.; Sneddon, Julie B.; Parmigiani, Giovanni: When should one subtract background fluorescence in 2-color microarrays? (2007)
  15. Wallenstein, Sylvan; Berger, Agnes: Weighted logrank tests to detect a transient improvement in survivorship (1997)