References
- Scott D, Sheather S. Kernel density estimation with binned data. Comm Statist Theory Methods. 1985;14:1353–1359. doi: 10.1080/03610928508828980
- Scott D. Average shifted histograms: effective non-parametric density estimators in several dimensions. Ann Stat. 1985;13:1024–1040. doi: 10.1214/aos/1176349654
- Silverman B. Density estimation for statistics and data analysis, monographs on statistics and applied probability. London: Chapman and Hall; 1986.
- Härdle W, Scott D. Smoothing in low and high dimensions by weighted averaging using rounded points. Comput Statist. 1992;7:97–128.
- Wand M, Jones M. Kernel smoothing. London: Chapman and Hall; 1995.
- Wang B, Wertelecki W. Density estimation for data with rounding errors. Comput Statist Data Anal. 2013;65:4–12. doi: 10.1016/j.csda.2012.02.016
- Scott DW, Scott WR. Smoothed histograms for frequency data on irregular intervals. Amer Stat. 2008;62:256–261. doi: 10.1198/000313008X335581
- Ramberg JS, Schmeiser BW. An approximate method for generating asymmetric random variables. Commun ACM. 1974;17(2):78–82. doi: 10.1145/360827.360840
- Tukey J. The practical relationship between the common transformations of percentages of counts and of amounts. Technical Report 36 Statistical Techniques Research Group, Princeton University1960.
- Ramberg JS, Tadikamalla PR, Dudewicz EJ, Mykytka EF. A probability distribution and its uses in fitting data. Technometrics. 1979;21:201–214. doi: 10.1080/00401706.1979.10489750
- Freimer M, Mudholkar GS, Kollia G, Lin CT. A study of the generalized Tukey lambda family. Commun Stat-Theor M. 1988;17:3547–3567. doi: 10.1080/03610928808829820
- Su S. Numerical maximum log likelihood estimation for generalized lambda distributions. Comput Stat Data Anal. 2007;51(8):3983–3998. doi: 10.1016/j.csda.2006.06.008
- Öztürk A, Dale RF. Least squares estimation of the parameters of the generalized lambda distribution. Technometrics. 1985;27(1):81–84. doi: 10.1080/00401706.1985.10488017
- Hosking J. L-moments: Analysis and estimation of distributions using linear combinations of order statistics. J Royal Stat Soc, Ser B. 1990;52:105–124.
- Karvanen J, Nuutinen A. Characterizing the generalized lambda distribution by l-moments. Comput Stat Data Anal. 2008;52:1971–1983. doi: 10.1016/j.csda.2007.06.021
- Karian Z, Dudewicz E. Comparison of GLD fitting methods: superiority of percentile fits to moments in l2 norm. J Iranian Statist Soc. 2003;2:171–187.
- Karian Z, Dudewicz E. Handbook of fitting statistical distributions with R. Boca Raton, FL: Chapman and Hall/CRC; 2011.
- Hahn G, Shapiro S. Statistical models in engineering. New York, NY: Wiley; 1967.
- U.S. census bureau. 2008–2012 american community survey, 2008–2012. Available from: http://factfinder2.census.gov/
- Dempster A, Laird N, Rubin D. Maximum likelihood from incomplete data via the em algorithm. J R Stat Soc B. 1977;39:1–38.
- McLachlan GJ, Jones PN. Fitting mixture models to grouped and truncated data via the EM algorithm. Biometrics. 1988;44:571–578. doi: 10.2307/2531869
- Jones B, McLachlan G. Maximum likelihood estimation from grouped and truncated data with finite normal mixture models. Appl Statist. 1990;39(2):273–312. doi: 10.2307/2347776
- Ning W, Gao Y, Dudewicz EJ. Fitting mixture distributions using generalized lambda distributions and comparison with normal mixtures. Am J Math Manage Sci. 2008;28(1–2):81–99. Available from: http://dx.doi.org/10.1080/01966324.2008.10737718