Results 51 to 60 of about 1,574 (90)

Comparison of Spline Methods for estimating Nonparametric Regression Curve [PDF]

المجلة العراقية للعلوم الاحصائية, 2005
This research is focusing on methods related to smoothing Nonparametric Regression Functions. This is for the purpose of producing the best methods convenient for various methods.
doaj   +1 more source

npbr: A Package for Nonparametric Boundary Regression in R

Journal of Statistical Software, 2017
The package npbr is the first free specialized software for data edge and frontier analysis in the statistical literature. It provides a variety of functions for the best known and most innovative approaches to nonparametric boundary estimation.
Abdelaati Daouia, Thibault Laurent, Hohsuk Noh   +2 more
doaj   +1 more source

Broadcasted nonparametric tensor regression

Journal of the Royal Statistical Society Series B: Statistical Methodology
Abstract We propose a novel use of a broadcasting operation, which distributes univariate functions to all entries of the tensor covariate, to model the nonlinearity in tensor regression nonparametrically. A penalized estimation and the corresponding algorithm are proposed.
Ya Zhou, Raymond K W Wong, Kejun He
openaire   +2 more sources

Nonparametric Regression [PDF]

, 2009
Paul P. B. Eggermont, Vincent N. LaRiccia   +1 more
  +5 more sources

Nonparametric regression estimation using multivariable truncated splines for binary response data

MethodsX
In recent years, Truncated Spline estimators in nonparametric regression for quantitative data have gained significant attention. However, in practical applications, it is common to encounter situations where the response variable is qualitative (binary).
Afiqah Saffa Suriaslan, I Nyoman Budiantara, Vita Ratnasari   +2 more
doaj   +1 more source

Application of nonparametric regression in predicting traffic incident duration

Transport, 2018
Predicting the duration time of incidents is important for effective real-time Traffic Incident Management (TIM). In the current study, the k-Nearest Neighbor (kNN) algorithm is employed as a nonparametric regression approach to develop a traffic ...
Shi Wang, Ruimin Li, Min Guo
doaj   +1 more source

Application of the Scaling Functions to Nonparametric Regression [PDF]

Informatică economică, 2007
For estimating regression function we can use many proceedings. In this paper, we have chosen to apply scaling functions to the estimation of regression functions.
doaj  

Testing Heteroscedasticity in Nonparametric Regression Based on Trend Analysis

Journal of Applied Mathematics, 2014
We first propose in this paper a new test method for detecting heteroscedasticity of the error term in nonparametric regression. Some simulation experiments are then conducted to evaluate the performance of the proposed methodology. A real-world data set
Si-Lian Shen, Jian-Ling Cui, Chun-Wei Wang   +2 more
doaj   +1 more source

Spline Estimator in Multi-Response Nonparametric Regression Model

Jurnal Ilmu Dasar, 2010
In many applications two or more dependent variables are observed at several values of the independent variables, such as at time points. The statistical problems are to estimate functions that model their dependences on the independent variables, and to
Budi Lestari, Nyoman Budiantara, Sony Sunaryo, Muhammad Mashuri   +3 more
doaj  

MODELING OPEN UNEMPLOYMENT RATE IN KALIMANTAN ISLAND USING NONPARAMETRIC REGRESSION WITH FOURIER SERIES ESTIMATOR

Barekeng
Nonparametric regression is a regression approach that is used to determine the relationship between the response variable and the predictor variable if the shape of the regression curve is unknown.
Rahmania Rahmania, Sifriyani Sifriyani, Andrea Tri Rian Dani   +2 more
doaj   +1 more source