Results 21 to 30 of about 5,204,898 (289)

An Improved Power Law for Nonlinear Least-Squares Fitting?

Data, 2017
Models based on a power law are prevalent in many areas of study. When regression analysis is performed on data sets modeled by a power law, the traditional model uses a lead coefficient.
Benjamin Helyer, Michael Courtney
doaj   +1 more source

Incrementally Solving Nonlinear Regression Tasks Using IBHM Algorithm

Journal of Telecommunications and Information Technology, 2023
This paper considers the black-box approximation problem where the goal is to create a regression model using only empirical data without incorporating knowledge about the character of nonlinearity of the approximated function.
Paweł Zawistowski, Jarosław Arabas
doaj   +1 more source

Determination of the critical period of weed control in corn using a thermal basis Determinação do período crítico de controle de plantas daninhas em milho utilizando uma base térmica

Pesquisa Agropecuária Brasileira, 1999
Field studies were conducted over 3 years in southeast Buenos Aires, Argentina, to determine the critical period of weed control in maize (Zea mays L.).
Francisco Bedmar, Pablo Manetti, Gloria Monterubbianesi   +2 more
doaj   +1 more source

Evaluation of the paraoxonase-1 kinetic parameters of the lactonase activity by nonlinear fit of progress curves

Journal of Enzyme Inhibition and Medicinal Chemistry, 2020
Although paraoxonase-1 (PON1) activity has been demonstrated to be a reliable biomarker of various diseases, clinical studies have been based only on relative comparison of specific enzyme activities, which capture differences mainly due to (usually ...
Marko Goličnik, Aljoša Bavec
doaj   +1 more source

Parametric Elliptical Regression Quantiles

Revstat Statistical Journal, 2020
The article extends linear and nonlinear quantile regression to the case of vector responses by generalizing multivariate elliptical quantiles to a regression context.
Daniel Hlubinka , Miroslav Šiman
doaj   +1 more source

Nonlinear stochastic modelling with Langevin regression [PDF]

Proceedings of the Royal Society A, 2020
Many physical systems characterized by nonlinear multiscale interactions can be modelled by treating unresolved degrees of freedom as random fluctuations.
Jared L. Callaham, Jean-Christophe Loiseau, Georgios Rigas, S. Brunton   +3 more
semanticscholar   +1 more source

The regression Tsetlin machine: a novel approach to interpretable nonlinear regression

Philosophical Transactions of the Royal Society A, 2019
Relying simply on bitwise operators, the recently introduced Tsetlin machine (TM) has provided competitive pattern classification accuracy in several benchmarks, including text understanding.
K. Darshana Abeyrathna, Ole-Christoffer Granmo, Xuan Zhang, Lei Jiao, Morten Goodwin   +4 more
semanticscholar   +1 more source

Overdispersed Nonlinear Regression Models

Austrian Journal of Statistics
In this paper we propose nonlinear regression models in the biparametric family of distributions. In this class of models we propose two new classes of overdispersed nonlinear regression models: the first, defined from the overdispersion family of ...
Edilberto Cepeda-Cuervo, María Victoria Cifuentes   +1 more
doaj   +1 more source

Intervalo hídrico ótimo na avaliação de sistemas de pastejo contínuo e rotacionado Least limiting water range in the evaluation of continuous and short-duration grazing systems

Revista Brasileira de Ciência do Solo, 2004
A qualidade física do solo sob sistemas de pastejo contínuo e rotacionado foi avaliada pelo Intervalo Hídrico Ótimo (IHO). A amostragem foi realizada na área experimental da Embrapa Gado de Corte. Foi estudado um Latossolo Vermelho distrófico.
T. P. Leão, A. P. Silva, M. C. M. Macedo, S. Imhoff, V. P. B. Euclides   +4 more
doaj   +1 more source

Non-crossing nonlinear regression quantiles by monotone composite quantile regression neural network, with application to rainfall extremes

Stochastic environmental research and risk assessment (Print), 2018
The goal of quantile regression is to estimate conditional quantiles for specified values of quantile probability using linear or nonlinear regression equations. These estimates are prone to “quantile crossing”, where regression predictions for different
Alex J. Cannon
semanticscholar   +1 more source