15 papers · ranked by Valyu relevance
Andrej-Nikolai Spiess, Natalie Neumeyer
Background It is long known within the mathematical literature that the coefficient of determination R2 is an inadequate measure for the goodness of fit in nonlinear models. Nevertheless, it is still frequently used within pharmacological and biochemical literature for the analysis and interpretation of nonlinear…
Timothy E. O’Brien, Jack W. Silcox
Use of nonlinear statistical methods and models are ubiquitous in scientific research. However, these methods may not be fully understood, and as demonstrated here, commonly-reported parameter p-values and confidence intervals may be inaccurate. The gentle introduction to nonlinear regression modelling and…
Turki Alsuwian, Arslan Ahmed Amin, Muhammad Sajid Iqbal, Muhammad Bilal Qadir + 3 more
'Muhammad Bilal Qadir' 'Saleh Almasabi' 'Mohammed Jalalah' 'Alessandro Borri'] Internal Combustion (IC) engines are prevalent in the process sector, and maintaining sufficient Air-Fuel Ratio (AFR) regulation in their fuel system is crucial for enhanced engine performance, fuel economy, and environmental safety. Faults…
Noah A. Schuster, Judith J. M. Rijnhart, Jos W. R. Twisk, Martijn W. Heymans
'Martijn W. Heymans'] Objective Traditional methods to deal with non-linearity in regression analysis often result in loss of information or compromised interpretability of the results. A recommended but underutilized method for modeling non-linear associations in regression models is spline functions. We explain…
Alexander Caicedo, Carolina Varon, Sabine Van Huffel, Johan A. K. Suykens + 1 more
'Johan A. K. Suykens' 'Antonio Agudo'] Kernel regression models have been used as non-parametric methods for fitting experimental data. However, due to their non-parametric nature, they belong to the so-called “black box” models, indicating that the relation between the input variables and the output, depending on the…
Krzysztof Wiktorowicz, Krzysztof Przednowek, Lesław Lassota, Tomasz Krzeszowski
'Tomasz Krzeszowski'] This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers' training events and they are used to predict the result over a 3 km race based on training loads. The…
William Casey, Leigh Metcalf, Shirshendu Chatterjee, Heeralal Janwa + 3 more
Many real-world problems feature nonlinear dynamic processes. Classical mathematical models may be adequate to describe a single dynamic process in isolation, but can be easily undermined by two natural and simple kinds of phenomenological variations: the emergence (or activation) of an additional dynamic process, and…
Nicholas C Chesnaye, Merel van Diepen, Friedo Dekker, Carmine Zoccali + 2 more
'Carmine Zoccali' 'Kitty J Jager' 'Vianda S Stel'] Title: ABSTRACT True linear relationships are rare in clinical data. Despite this, linearity is often assumed during analyses, leading to potentially biased estimates and inaccurate conclusions. In this introductory paper, we aim to first describe-in a non-mathematical…
Noah A. Schuster, Judith J. M. Rijnhart, Lisa C. Bosman, Jos W. R. Twisk + 2 more
'Jos W. R. Twisk' 'Thomas Klausch' 'Martijn W. Heymans'] Background Confounding is a common issue in epidemiological research. Commonly used confounder-adjustment methods include multivariable regression analysis and propensity score methods. Although it is common practice to assess the linearity assumption for the…
Larissa Raffaela Trindade Borges, Felipe Augusto Fernandes, Alan Freire, Brennda Paula Gonçalves Araujo + 2 more
Growth curve modeling is a fundamental tool in animal production, allowing the analysis of the relationship between body weight and age through nonlinear statistical models. Traditionally, this curve has been obtained using the longitudinal method, which requires repeated measurements of the same individuals from birth…
Mona Mahmoud Abo El Nasr, Alaa A. Abdelmegaly, Doaa A. Abdo
This paper provides a comprehensive analysis of linear regression models, focusing on addressing multicollinearity challenges in breast cancer patient data. Linear regression methodologies, including GAM, Beta, GAM Beta, Ridge, and Beta Ridge, are compared using two statistical criteria. The study, conducted with R…
Afiqah Saffa Suriaslan, I Nyoman Budiantara, Vita Ratnasari
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). As a result, Truncated Spline nonparametric regression models…
Trung C. Phan, Adrian Pranata, Joshua Farragher, Adam Bryant + 3 more
Machine learning (ML) algorithms are crucial within the realm of healthcare applications. However, a comprehensive assessment of the effectiveness of regression algorithms in predicting alterations in lifting movement patterns has not been conducted. This research represents a pilot investigation using regression-based…
Kimmo Eriksson, Olle Häggström, Robert J. van Beers
In this paper we review, and elaborate on, the literature on a regression artifact related to Lord’s paradox in a continuous setting. Specifically, the question is whether a continuous property of individuals predicts improvement from training between a pretest and a posttest. If the pretest score is included as a…
Fatih Gurcan, Carlos Fernandez-Lozano
Background The continuous increase in carbon dioxide (CO2) emissions from fuel vehicles generates a greenhouse effect in the atmosphere, which has a negative impact on global warming and climate change and raises serious concerns about environmental sustainability. Therefore, research on estimating and reducing vehicle…