Tilted Nadaraya-Watson Regression Estimator
13th Chaotic Modeling and Simulation International Conference, CHAOS 2020
; : 797-803, 2021.
Article
in English
| Scopus | ID: covidwho-1607818
ABSTRACT
In nonparametric statistics the tilting techniques are sustainably used for adjusting an empirical distribution by replacing uniform distribution of weights by general multinomial distribution. In this paper a tilting approach has been used for minimizing “the distance” to an infinite order (IO) regression estimator, a comparator regression function estimator. We also provide the simulation study results illustrating the tilted version of the Nadaraya-Watson (N-W) estimator performs better than its classical analog (the N-W estimator) in terms of Median Integrated Squared Error (MISE). In addition, the performance of the tilted N-W regression function estimator has been examined using the Italy’s COVID-19 deaths data. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Databases of international organizations
Database:
Scopus
Language:
English
Journal:
13th Chaotic Modeling and Simulation International Conference, CHAOS 2020
Year:
2021
Document Type:
Article
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