The main purpose of mathematical model building while employing statistical data analysis
is to obtain high accuracy of approximation within the range of observed data and sufficient …

Mathematical models building is widely used in different branches of human activity to
describe statistical data obtained during observation of various phenomena. The main tool …

Abstract Modified Gauss and Gram–Schmidt methods are proposed for recursive estimation
of the parameters of sequentially complicated structures of regression models in observation …

Regression modeling is one of the most widely used statistical processes to estimate the
relationships between dependent and independent variables, which have been frequently …

This article deals with estimation of the regression function and its derivatives using local
polynomial fitting. An important question is: How to determine the order of the polynomial to …

Regression spline smoothing is a popular approach for conducting nonparametric
regression. An important issue associated with it is the choice of a" theoretically best" set of …

Additive models belong to the techniques of modern statistical learning; they are applicable
in many areas of prediction such as financial mathematics, computational biology, medicine …

A grid-search method of fitting segmented regression curves with unknown transition points
is described and compared with a standard method. It is shown to be suitable for fitting a …

In this article we introduce a graphical method for the test of the equality of two regression
curves. Our method is based on SiZer (SIgnificant ZERo crossing of the differences) …

Curve fitting is one of the procedures in data analysis and is helpful for prediction analysis
showing graphically how the data points are related to one another whether it is in linear or …