Securing Density Estimates via Smooth Moment-Based Empirical Distribution Function Approximants
نویسندگان
چکیده
This paper proposes an adaptive density estimation procedure that hinges on securing moment-based approximants of certain splines passing through particular points are obtained from appropriately adjusted and truncated empirical distribution function. More specifically, a four-parameter beta estimate is initially fitted to the data in order determine endpoints which combined points. Interpolants continuity-corrected function evaluated at these then approximated by smooth functions involving polynomials. As matter course, estimates differentiation. Any quantile corresponding can thereby be directly associated functions. The Cramér-von Mises goodness-of-fit statistic utilized as measure accuracy. Three illustrative examples presented.
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ژورنال
عنوان ژورنال: Journal of the Indian Society for Probability and Statistics
سال: 2022
ISSN: ['2364-9569']
DOI: https://doi.org/10.1007/s41096-022-00119-4