Results 11 to 20 of about 7,819,841 (287)
Machine Learning, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Niels Landwehr +2 more
openaire +4 more sources
Analysis of logistic growth models [PDF]
Mathematical Biosciences, 2002 A variety of growth curves have been developed to model both unpredated, intraspecific population dynamics and more general biological growth. Most predictive models are shown to be based on variations of the classical Verhulst logistic growth equation. We review and compare several such models and analyse properties of interest for these.
A Tsoularis
exaly +3 more sources
Endogeneity in Logistic Regression Models
Emerging Infectious Diseases, 2005 To the Editor: Ethelberg et al. (1) report on a study of the determinants of hemolytic uremic syndrome resulting from Shiga toxin–producing Escherichia coli. The dataset is relatively small, and the authors use stepwise logistic regression models to detect small differences.
George Avery +2 more
doaj +3 more sources
Properties of estimators of parameters in logistic regression models [PDF]
, 1985 Properties of various types of estimators of the regression coefficients in linear logistic regression models are considered. The estimators include those based on maximum likelihood, minimum chi-square and weighted least squares.
Al-Sarraf, Z, Young, D H
core +6 more sources
Quantitative Models of Fungi Interaction--based on Logistic models [PDF]
E3S Web of Conferences, 2021 As the key medium for decomposing wood fibers, fungi play a vital role in promoting the carbon cycle. The purpose of this paper is to establish mathematic models describing the process of fungi decomposing litter and wood fiber. The paper comprehensively
Zhang Yunfei
doaj +1 more source
The extreme residuals in logistic regression models [PDF]
, 1985 Goodness of fit tests for logistic regression models using extreme residuals are considered. Moment properties of the Pearson residuals are developed and used to define modified residuals, for the cases when the model fit is made by maximum ...
Z. Al-sarraf +3 more
core +6 more sources
Variable Selection for Spatial Logistic Autoregressive Models
Mathematics, 2022 When the spatial response variables are discrete, the spatial logistic autoregressive model adds an additional network structure to the ordinary logistic regression model to improve the classification accuracy. With the emergence of high-dimensional data
Jiaxuan Liang +4 more
doaj +1 more source
Group Logistic Regression Models with lp,q Regularization
Mathematics, 2022 In this paper, we proposed a logistic regression model with lp,q regularization that could give a group sparse solution. The model could be applied to variable-selection problems with sparse group structures. In the context of big data, the solutions for
Yanfang Zhang, Chuanhua Wei, Xiaolin Liu
doaj +1 more source
On the Complexity of Logistic Regression Models [PDF]
Neural Computation, 2019 We investigate the complexity of logistic regression models, which is defined by counting the number of indistinguishable distributions that the model can represent (Balasubramanian, 1997 ). We find that the complexity of logistic models with binary inputs depends not only on the number of parameters but also on the distribution of inputs in a ...
Nicola Bulso +2 more
openaire +5 more sources
Machine Learning-based Classifiers for the Prediction of Low Birth Weight [PDF]
Healthcare Informatics Research, 2023 Objectives Low birth weight (LBW) is a global concern associated with fetal and neonatal mortality as well as adverse consequences such as intellectual disability, impaired cognitive development, and chronic diseases in adulthood.
Mahya Arayeshgari +4 more
doaj +1 more source