Data-Driven Bandwidth Selection for Recursive Kernel Density Estimators Under Double Truncation
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DOI: 10.1007/s13571-018-0165-2
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- Pao-sheng Shen, 2010. "Nonparametric analysis of doubly truncated data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(5), pages 835-853, October.
- Yousri Slaoui, 2015. "Plug-in bandwidth selector for recursive kernel regression estimators defined by stochastic approximation method," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(4), pages 483-509, November.
- Moreira, Carla & de Uña-Álvarez, Jacobo & Crujeiras, Rosa M., 2010. "DTDA: An R Package to Analyze Randomly Truncated Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 37(i07).
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Cited by:
- Ye Tian & Yasunari Yokota, 2019. "Estimating the Major Cluster by Mean-Shift with Updating Kernel," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
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Keywords
Density estimation; Stochastic approximation algorithm; Smoothing; Curve fitting; Double truncated data.;All these keywords.
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