Results 51 to 60 of about 501,333 (190)

EVALUATION OF THE FLEXIBILITY OF NADARAYA-WATSON KERNEL AND PENALIZED SPLINE ESTIMATORS IN BIVARIATE RESPONSE NONPARAMETRIC REGRESSION MODELS

Barekeng
Nonparametric regression is a flexible approach used when the functional relationship between predictors and responses is unknown. In the context of multiple responses, bivariate nonparametric regression allows modeling two correlated response variables,
Cinta Rizki Oktarina, Sigit Nugroho, Idhia Sriliana   +2 more
doaj   +1 more source

Adaptive Estimation for Weakly Dependent Functional Times Series

Journal of Time Series Analysis, Volume 47, Issue 5, Page 1013-1027, September 2026.
ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro, Valentin Patilea, Myriam Vimond   +2 more
wiley   +1 more source

On Metric Choice in Dimension Reduction for Fréchet Regression

International Statistical Review, Volume 94, Issue 2, Page 325-346, August 2026.
Summary Fréchet regression is becoming a mainstay in modern data analysis for analysing non‐traditional data types belonging to general metric spaces. This novel regression method is especially useful in the analysis of complex health data such as continuous monitoring and imaging data.
Abdul‐Nasah Soale, Congli Ma, Siyu Chen, Obed Koomson   +3 more
wiley   +1 more source

A Comparative Review of Specification Tests for Diffusion Models

International Statistical Review, Volume 94, Issue 2, Page 347-381, August 2026.
Summary Diffusion models play an essential role in modelling continuous‐time stochastic processes in the financial field. Therefore, several proposals have been developed in the last decades to test the specification of stochastic differential equations.
A. López‐Pérez, D. Diz‐Castro, M. Febrero‐Bande, W. González‐Manteiga   +3 more
wiley   +1 more source

Iterative Bias Reduction Multivariate Smoothing in R: The ibr Package

Journal of Statistical Software, 2017
In multivariate nonparametric analysis curse of dimensionality forces one to use large smoothing parameters. This leads to a biased smoother. Instead of focusing on optimally selecting the smoothing parameter, we fix it to some reasonably large value to ...
Pierre-André Cornillon, Nicolas Hengartner, Eric Matzner-Løber   +2 more
doaj   +1 more source

Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in…finite order [PDF]

SSRN Electronic Journal, 2016
36 ...
Hong, Seok Young, Linton, Oliver Bruce
openaire   +3 more sources

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches

Journal of Forecasting, Volume 45, Issue 4, Page 1579-1600, July 2026.
ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann, Mawuli Segnon, Timo Wiedemann   +2 more
wiley   +1 more source

ESTIMATOR NADARAYA-WATSON DENGAN KERNEL ORDE BERHINGGA DAN TAK HINGGA [PDF]

, 2015
This article compared the performance between finite order kernel (normal) and infinite order kernel (sinus and cosinus) in Nadaraya Watson estimator by comparing the MSE values.
Apriani, Maria Suci
core  

Automated Bandwidth Selection for Inference in Linear Models With Time‐Varying Coefficients

Journal of Time Series Analysis, Volume 47, Issue 4, Page 854-875, July 2026.
ABSTRACT The problem of selecting the smoothing parameter, or bandwidth, for kernel‐based estimators of time‐varying coefficients in linear models with possibly endogenous explanatory variables is considered. We examine automated bandwidth selection by means of cross‐validation, a nonparametric variant of Akaike's information criterion, and bootstrap ...
Charisios Grivas, Zacharias Psaradakis
wiley   +1 more source

INTRODUCTION TO THE VARIANCE-STABILIZING BANDWIDTH FOR THE NADARAYA-WATSON REGRESSION ESTIMATOR

INTRODUCTION TO THE VARIANCE-STABILIZING BANDWIDTH FOR THE NADARAYA-WATSON REGRESSION ESTIMATOR
In linear regression under heteroscedastic variances, Aitken estimator is employed to account for the differences in variances. Employing the same principle, we propose the Nadaraya-Watson regression estimator with variable variance-stabilizing bandwidth (VS bandwidth) that minimizes asymptotic MISE (AMISE) while maintaining asymptotic homoscedasticity.
金澤, 雄一郎, ニシダ, キヘイジ, Nishida, Kiheiji, 西田, 喜平次, Kanazawa, Yuichiro, カナザワ, ユウイチロウ   +5 more
openaire   +2 more sources