References
- Chang, W., Cheng, J., Allaire, J. J., Xie, Y., & McPherson, J. (2017). shiny: Web Application Framework for R, r package version 1.0.5.
- R Core Team. (2017). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
- Freimer, M., Kollia, G., Mudholkar, G. S., & Lin, C. T. (1988). A study of the generalized Tukey lambda family. Communications in Statistics-Theory and Methods, 17, 3547–11. doi:10.1080/03610928808829820
- Gilchrist, W. (2000). Statistical modelling with quantile functions. Florida: CRC Press.
- Hellinger, E. (1909). Neue begründung der theorie quadratischer formen von unendlichvielen veränderlichen. Journal für die reine und angewandte Mathematik, 136, 210–271.
- Karian, Z., & Dudewicz, E. (1999). Fitting the generalized lambda distribution to data: A method based on percentiles. Communications in Statistics-Simulation and Computation, 28(3), 793–819. doi:10.1080/03610919908813579
- Karian, Z. A., & Dudewicz, E. J. (2003). Comparison of GLD fitting methods: Superiority of percentile fits to moments in L2 norm.
- Karian, Z. A., & Dudewicz, E. J. (2016). Handbook of fitting statistical distributions with R. New York, NY: Chapman and Hall/CRC.
- Lakhany, A., & Mausser, H. (2000). Estimating the parameters of the generalized lambda distribution. Algo Research Quarterly, 3(3), 47–58.
- Parzen, E. (1979). Nonparametric statistical data modeling. Journal of the American Statistical Association, 74, 105–121. doi:10.1080/01621459.1979.10481621
- Pfaff, B. (2016). Financial risk modelling and portfolio optimization with R. UK: John Wiley & Sons.
- Ramberg, J. S., & Schmeiser, B. W. (1974). An approximate method for generating asymmetric random variables. Communications of the ACM, 17(2), 78–82. doi:10.1145/360827.360840
- Sharma, D., & Chakrabarty, T. K. (2017). Some general results on quantile functions for the generalized beta family. Statistics, Optimization & Information Computing, 5(4), 360–377. doi:10.19139/soic.v5i4.312
- Staudte, R. G. (2017). The shapes of things to come: Probability density quantiles. Statistics, 51, 782–800. doi:10.1080/02331888.2016.1277225
- Staudte, R. G., & Sheather, S. J. (1990). Robust estimation and testing (Vol. 918). New York, NY: John Wiley & Sons.
- Staudte, R. G., & Xia, A. (2018). Divergence from, and convergence to, uniformity of probability density quantiles. Entropy, 20(5). doi:10.3390/e20050317
- Tarsitano, A. (2005). Estimation of the generalized lambda distribution parameters for grouped data. Communications in Statistics—Theory and Methods, 34(8), 1689–1709. doi:10.1081/STA-200066334
- Tukey, J. W. (1965). Which part of the sample contains the information? Proceedings of the National Academy of Sciences, 53, 127–134.
- Venables, W. N., & Ripley, B. D. (2002). Modern applied statistics with S (4th ed.). New York: Springer. ISBN 0-387-95457-0.
- Wang, B. (2015). bda: Density Estimation for Grouped Data, R package version 5.1.6.. doi:10.1094/PDIS-09-14-0954-PDN