This paper investigates various regression models to predict the compressor and turbine
map parameters. To this end, we used the data measured from two different types of …

Abstract In recent years, Thailand Government has made ambitious targets for biofuels and
the demand for biofuels has increased. This study estimates the long-term factors that affect …

Nonlinear regression models are widely used for modeling of stochastic phenomena and
the estimating parameters problem plays a central role in the inference in nonlinear …

The procedures to estimate the parameters are important in many scientific fields that are
required to develop mathematical models. Thus, this paper is proposed as a Gravitational …

Nonlinear models are commonly used for analyzing real-life data such as in medicine,
engineering, and economics. To make efficient inferences about model parameter …

Nonlinear models are usually encountered in various areas including experimental studies
such as physics, chemistry, biology etc. Ordinary least squares is one of the most widely …

Ordinary least squares method is usually used for parameter estimation in multiple linear
regression models when all regression assumptions are satisfied. One of the problems in …

A seemingly unrelated regression (SUR) model is defined by a system of linear regression
equations in which the disturbances are contemporaneously correlated across equations …

The article introduces a method of checking the operability of automotive equipment valve
blocks on the basis of automatized definition of parameters of a linearity equivalent circuit of …

Sinusoidal functions are widely used in many areas, such as physics, engineering, and
gene expression to describe correlated data along with time. A sinusoidal model with …