Results 11 to 20 of about 208,599 (260)
Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models [PDF]
, 2020 Penalization of the likelihood by Jeffreys' invariant prior, or by a positive power thereof, is shown to produce finite-valued maximum penalized likelihood estimates in a broad class of binomial generalized linear models.
Firth, David, Kosmidis, Ioannis
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Normal-Power-Logistic Distribution: Properties and Application in Generalized Linear Model
Journal of the Indian Society for Probability and Statistics, 2022 The applications of Normal distribution in literature are verse, the new modified univariate normal power distribution is a new distribution which is adequate for modelling bimodal data. There are many data that would have been modelled by normal distribution, but because of their bimodality, they are not, since normal distribution is unimodal. In this
Matthew I. Ekum +2 more
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BMC Medical Research Methodology, 2017 Background The analysis of correlated binary data is commonly addressed through the use of conditional models with random effects included in the systematic component as opposed to generalized estimating equations (GEE) models that addressed the random ...
Jie Pu, Di Fang, Jeffrey R. Wilson
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Analysis of neonatal clinical trials with twin births
BMC Medical Research Methodology, 2009 Background In neonatal trials of pre-term or low-birth-weight infants, twins may represent 10–20% of the study sample. Mixed-effects models and generalized estimating equations are common approaches for handling correlated continuous or binary data ...
Shaffer Michele L +2 more
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K-L Estimator: Dealing with Multicollinearity in the Logistic Regression Model
Mathematics, 2023 Multicollinearity negatively affects the efficiency of the maximum likelihood estimator (MLE) in both the linear and generalized linear models. The Kibria and Lukman estimator (KLE) was developed as an alternative to the MLE to handle multicollinearity ...
Adewale F. Lukman +5 more
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Applied Sciences, 2023 The current research has aimed to investigate and develop machine-learning approaches by using the data in the dataset to be applied to classify location-based social network data and predict user activities based on the nature of various locations (such
Naimat Ullah Khan +4 more
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Grid multi-category response logistic models. [PDF]
, 2015 BackgroundMulti-category response models are very important complements to binary logistic models in medical decision-making. Decomposing model construction by aggregating computation developed at different sites is necessary when data cannot be moved ...
Jiang, Wenchao +5 more
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Chain graph models of multivariate regression type for categorical data [PDF]
, 2011 We discuss a class of chain graph models for categorical variables defined by what we call a multivariate regression chain graph Markov property. First, the set of local independencies of these models is shown to be Markov equivalent to those of a chain ...
Lupparelli, Monia +1 more
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A generalized Liu-type estimator for logistic partial linear regression model with multicollinearity
AIMS Mathematics, 2023 <abstract><p>This paper is concerned with proposing a generalized Liu-type estimator (GLTE) to address the multicollinearity problem of explanatory variable of the linear part in the logistic partially linear regression model. Using the profile likelihood method, we propose the GLTE as a general class of Liu-type estimator, which includes ...
Dayang Dai, Dabuxilatu Wang
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Robust inference for generalized linear models with application to logistic regression [PDF]
Statistics & Probability Letters, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
ADIMARI, GIANFRANCO, VENTURA, LAURA
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