Piecewise Linear Continuous Estimators of the Quantile Function
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-73249-3_9
Reference21 articles.
1. Aragon, Y., Daouia, A., & Thomas-Agnan, C. (2005). Nonparametric frontier estimation: A conditional quantile-based approach. Econometric Theory, 21(2), 358–389.
2. Azzalini, A. (1981). A note on the estimation of a distribution function and quantiles by a kernel method. Biometrika, 68(1), 326–328.
3. Babu, G. J., Canty, A. J., & Chaubey, Y. P. (2002). Application of Bernstein polynomials for smooth estimation of a distribution and density function. Journal of Statistical Planning and Inference, 105(2), 377–392.
4. Blanke, D., & Bosq, D. (2018). Polygonal smoothing of the empirical distribution function. Statistical Inference for Stochastic Processes, 21(2), 263–287.
5. Cheng, C., & Parzen, E. (1997). Unified estimators of smooth quantile and quantile density functions. Journal of Statistical Planning and Inference, 59(2), 291–307.
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