This paper presents a systematic approach for representing and estimating the Cartesian
positioning errors of robot manipulators with analytical functions such as Fourier …

Additive models with backfitting algorithms are popular multivariate nonparametric fitting
techniques. However, the inferences of the models have not been very well developed, due …

In this article, we propose a new method in estimating non parametric regression curve. This
method combines the smoothing Spline and Kernel functions. Estimation of the estimator is …

This paper aims to present an overview of Semiparametric additive models. An estimation of
the finite‐parameters of semiparametric regression models that involve additive …

A commonly used semiparametric partial linear model is considered. We propose analyzing
this model using a difference based approach. The procedure estimates the linear …

A regression model, in general, describes relationship between response and predictor
variables. Suppose that iy is response variable and it is predictor variable, then for n …

Nonparametric additive models are garnering increasing attention in applied research
across fields like statistics and economics, attributed to their distinct interpretability …

The purpose of this study is to propose an appropriate model to predict chemical
composition during water purification at the Regional Water Company (PDAM) Surabaya, in …

In this article, we propose a new method of selecting smoothing parameters in
semiparametric regression. This method is used in semiparametric regression estimation …

In data analysis using a nonparametric regression approach, we are often faced with the
problem of analyzing a set of data that has mixed patterns, namely, some of the data have a …