@inproceedings{3b71d9d9eed04b3da0b5d050eaaac2f7,
title = "Tilted Nadaraya-Watson regression estimator",
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{\textquoteright}s COVID-19 deaths data.",
keywords = "Nadaraya-Watson estimator, Tilted Nadaraya-Watson estimator, Infinite order estimator, Kernel estimator, Trapezoidal kernel, Cross-validation function, MISE, ISE",
author = "Shakeri, {Mohammad T.} and Farzaneh Boroumand and Hassan Doosti and Nino Kordzakhia and Mahdi Salehi",
year = "2021",
doi = "10.1007/978-3-030-70795-8_56",
language = "English",
isbn = "9783030707941",
series = "Springer Proceedings in Complexity",
publisher = "Springer, Springer Nature",
pages = "797--803",
editor = "Skiadas, {Christos H.} and Yiannis Dimotikalis",
booktitle = "13th Chaotic Modeling and Simulation International Conference",
address = "United States",
note = "13th Chaotic Modeling and Simulation International Conference, CHAOS 2020 ; Conference date: 09-06-2020 Through 12-06-2020",
}