Partial least-squares regression as a tool to retrieve gas concentrations in mixtures detected using quartz-enhanced photoacoustic spectroscopy
We report on a statistical tool based on partial least-squares regression (PLSR) able to
retrieve single-component concentrations in a multiple-gas mixture characterized by …
retrieve single-component concentrations in a multiple-gas mixture characterized by …
On a partial least squares regression model for asymmetric data with a chemical application in mining
In chemometrical applications, covariates in regression models are often correlated, causing
a collinearity problem that can be solved by partial least squares (PLS) regression. In …
a collinearity problem that can be solved by partial least squares (PLS) regression. In …
The unit generalized half-normal quantile regression model: formulation, estimation, diagnostics, and numerical applications
In this paper, we propose and derive a new regression model for response variables defined
on the open unit interval. By reparameterizing the unit generalized half-normal distribution …
on the open unit interval. By reparameterizing the unit generalized half-normal distribution …
An EEG-based stereoscopic research of the PSD differences in pre and post 2D&3D movies watching
Despite knowing the reality of three-dimensional (3D) technology in the form of eye fatigue,
this technology continues to be retained by people (especially the young community). To …
this technology continues to be retained by people (especially the young community). To …
Log‐symmetric regression models: information criteria and application to movie business and industry data with economic implications
This work deals with log‐symmetric regression models, which are particularly useful when
the response variable is continuous, strictly positive, and following an asymmetric …
the response variable is continuous, strictly positive, and following an asymmetric …
An errors-in-variables model based on the Birnbaum–Saunders distribution and its diagnostics with an application to earthquake data
Regression modelling where explanatory variables are measured with error is a common
problem in applied sciences. However, if inappropriate analysis methods are applied, then …
problem in applied sciences. However, if inappropriate analysis methods are applied, then …
Application of the partial least square regression method in determining the natural background of soil heavy metals: A case study in the Songhua River basin, China
Y Sun, Y Zhao, L Hao, X Zhao, J Lu, Y Shi, C Ma… - Science of The Total …, 2024 - Elsevier
The “background” is an essential index for identifying anthropogenic inputs and potential
ecological risks of soil heavy metals. However, the lithology of bedrock can cause significant …
ecological risks of soil heavy metals. However, the lithology of bedrock can cause significant …
On a new extreme value distribution: Characterization, parametric quantile regression, and application to extreme air pollution events
Extreme-value distributions are important when modeling weather events, such as
temperature and rainfall. These distributions are also important for modeling air pollution …
temperature and rainfall. These distributions are also important for modeling air pollution …
A study on computational algorithms in the estimation of parameters for a class of beta regression models
Beta regressions describe the relationship between a response that assumes values in the
zero-one range and covariates. These regressions are used for modeling rates, ratios, and …
zero-one range and covariates. These regressions are used for modeling rates, ratios, and …
Efficient cross-validatory algorithm for identifying dynamic nonlinear process models
Z Li, X Wang, U Kruger - Control Engineering Practice, 2021 - Elsevier
Kernel partial least squares (KPLS) is an effective nonlinear modeling technique for control
engineering applications, including model predictive control, process monitoring or general …
engineering applications, including model predictive control, process monitoring or general …