The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Data-Based Choice of Histogram Bin Width
Abstract
The most important parameter of a histogram is the bin width because it controls the tradeoff between presenting a picture with too much detail (“undersmoothing”) or too little detail (“oversmoothing”) with respect to the true distribution. Despite this importance there has been surprisingly little research into estimation of the “optimal” bin width. Default bin widths in most common statistical packages are, at least for large samples, quite far from the optimal bin width. Rules proposed by, for example, Scott lead to better large sample performance of the histogram, but are not consistent themselves. In this paper we extend the bin width rules of Scott to those that achieve root-n rates of convergence to the L 2-optimal bin width, thereby providing firm scientific justification for their use. Moreover, the proposed rules are simple, easy and fast to compute, and perform well in simulations.
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Cites
Approximation Theorems of Mathematical Statistics
Serfling, R. J. (1980) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316481 · Cited by 5,851
Multivariate Density Estimation: Theory, Practice, and Visualization
Scott, D. W. (1992) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316849 · Cited by 3,696
Wand, M. P., & Jones, M. C. (1995) · Springer eBooks · doi:10.1007/978-1-4899-4493-1 · Cited by 2,663
Self-citationA Reliable Data-Based Bandwidth Selection Method for Kernel Density Estimation
Sheather, S. J., & Jones, M. C. (1991) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1991.tb01857.x · Cited by 2,641
On optimal and data-based histograms
SCOTT, D. W. (1979) · Biometrika · doi:10.1093/biomet/66.3.605 · Cited by 1,819
The Choice of a Class Interval
Sturges, H. A. (1926) · Journal of the American Statistical Association · doi:10.1080/01621459.1926.10502161 · Cited by 1,764
On the histogram as a density estimator:L 2 theory
Freedman, D., & Diaconis, P. (1981) · Zeitschrift f�r Wahrscheinlichkeitstheorie und Verwandte Gebiete · doi:10.1007/bf01025868 · Cited by 1,601
Exact Mean Integrated Squared Error
Marron, J. S., & Wand, M. P. (1992) · The Annals of Statistics · doi:10.1214/aos/1176348653 · Cited by 750
Self-citationComparison of Data-Driven Bandwidth Selectors
Park, B. U., & Marron, J. S. (1990) · Journal of the American Statistical Association · doi:10.1080/01621459.1990.10475307 · Cited by 503
Estimation of integrated squared density derivatives
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Cited by
Chodera, J. D., Swope, W. C., Pitera, J. W., Seok, C., & Dill, K. A. (2007) · Journal of Chemical Theory and Computation · doi:10.1021/ct0502864 · Cited by 503
Describing and measuring the pathway to suicide attempts: A preliminary study
Millner, A. J., Lee, M. D., & Nock, M. K. (2017) · Suicide and Life-Threatening Behavior · doi:10.1111/sltb.12284 · Cited by 161
Confidence-based classifier design
Li, M., & Sethi, I. K. (2006) · Pattern Recognition · doi:10.1016/j.patcog.2006.01.010 · Cited by 61
Metadata
- Authors
- Wand, M. P.
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 1997-02
- Volume
- 51
- Issue
- 1
- Pages
- 59-64
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W2137460067
- Cited by
- 294
- References
- 16
- FWCI
- 4.27
- Type
- journal article
- Language
- en
- Open access
- closed
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