Results 81 to 90 of about 1,708 (192)

ESTIMATOR NADARAYA-WATSON DENGAN FUNGSI KERNEL NORMAL DAN FUNGSI KERNEL KUADRATIK

, 2022
The Human Development Index (HDI) is a comparative measurement of life expectancy, literacy, education and living standards for all countries around the world.
Janad, Nur Azizah, Handayani, Lilies, Tadale, Yudy Novindri, Putri, Saskia Amalia, Aristya, Ayudita Rahmi   +4 more
core   +1 more source

A Bistochastic Nonparametric Estimator [PDF]

We explore the relevance of adopting a bistochastic nonparametric estimator. This estimator has two main implications. First, the estimator reduces variability according to the robust criterion of second-order stochastic (and Lorenz) dominance. This is a
Rafael Salas, Juan Gabriel Rodríguez
core  

Survival Analysis as Imprecise Classification with Trainable Kernels

Mathematics
Survival analysis is a fundamental tool for modeling time-to-event data in healthcare, engineering, and finance, where censored observations pose significant challenges.
Andrei Konstantinov, Lev Utkin, Vlada Efremenko, Vladimir Muliukha, Alexey Lukashin, Natalya Verbova   +5 more
doaj   +1 more source

Nadaraya-Watson Density Estimation for Interval Censored Data

, 2007
This paper is concerned with the nonparametric estimation of a density function when the data are incomplete due to interval censoring.
Stoimenova, E.
core   +1 more source

Unveiling the paths of COVID-19 in a large city based on public transportation data. [PDF]

Sci Rep, 2023
Araújo JLB, Oliveira EA, Lima Neto AS, Andrade JS, Furtado V.   +4 more
europepmc   +2 more sources

BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect

Algorithms
A method for estimating the conditional average treatment effect under the condition of censored time-to-event data, called BENK (the Beran Estimator with Neural Kernels), is proposed.
Stanislav Kirpichenko, Lev Utkin, Andrei Konstantinov, Vladimir Muliukha   +3 more
doaj   +1 more source

A Note on the Unconditional Bias of the Nadaraya-Watson Regression Estimator

, 2018
In this note we investigate the order of the unconditional bias of the Nadarya-Watson (Nadaraya, 1964; Watson, 1964) estimator for a multivariate regression. Surprisingly, previous attempts in establishing this result are either imprecise and technically
Pelrine, Kellin
core   +1 more source

The Graphical Nadaraya-Watson Estimator in Latent Position Models

, 2023
Given a graph with a subset of labeled nodes, we are interested in the quality of the averaging estimator which for an unlabeled node predicts the average of the observations of its labeled neighbours. We rigorously study concentration properties, variance bounds and risk bounds in this context. While the estimator itself is very simple we believe that
Gjorgjevski, Martin, Keriven, Nicolas, Barthelme, Simon, de Castro, Yohann   +3 more
openaire   +1 more source

Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson Regression

, 2022
A new method for estimating the conditional average treatment effect is proposed in the paper. It is called TNW-CATE (the Trainable Nadaraya-Watson regression for CATE) and based on the assumption that the number of controls is rather large whereas the ...
Kirpichenko, Stanislav R., Konstantinov, Andrei V., Utkin, Lev V.   +2 more
core  

Weighted Nadaraya-Watson regression estimation

In this article, we study nonparametric estimation of regression function by using the weighted Nadaraya-Watson approach. We establish the asymptotic normality and weak consistency of the resulting estimator for [alpha]-mixing time series at both ...
Cai, Zongwu
core