Results 11 to 20 of about 1,583,424 (275)
Exact Hypothesis Tests for Log-linear Models with exactLoglinTest [PDF]
Journal of Statistical Software, 2006 This manuscript overviews exact testing of goodness of fit for log-linear models using the R package exactLoglinTest. This package evaluates model fit for Poisson log-linear models by conditioning on minimal sufficient statistics to remove nuisance ...
Brian Caffo
doaj +4 more sources
Modelling child anaemia and co-existing infections using log-linear models [PDF]
Malaria JournalBackground Uganda grapples with a considerable anaemia-malaria-fever burden, reporting approximate prevalence rates as high as 33%, 34%, and 37% in specific regions.
Grace Kakaire +3 more
doaj +2 more sources
Maximum likelihood estimation in log-linear models
Annals of Statistics, 2012 We study maximum likelihood estimation in log-linear models under conditional Poisson sampling schemes. We derive necessary and sufficient conditions for existence of the maximum likelihood estimator (MLE) of the model parameters and investigate ...
Fienberg, Stephen E. +1 more
core +5 more sources
Heatmaps for Patterns of Association in log-Linear Models
Socius, 2020 Log-linear models offer a detailed characterization of the association between categorical variables, but the breadth of their outputs is difficult to grasp because of the large number of parameters these models entail.
Mauricio Bucca
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Log-Linear Models for Gene Association. [PDF]
J Am Stat Assoc, 2009 We describe a class of log-linear models for the detection of interactions in high-dimensional genomic data. This class of models leads to a Bayesian model selection algorithm that can be applied to data that have been reduced to contingency tables using ranks of observations within subjects, and discretization of these ranks within gene/network ...
Hu J, Joshi A, Johnson VE.
europepmc +5 more sources
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1972 Summary Log-linear models are extensively used to analyse categorical and “stimulus-response” data. This paper gives an iterative procedure for obtaining maximum likelihood estimates of cell frequencies and of the parameters of a log-linear model in a multinomial experiment.
exaly +3 more sources
A conjugate prior for discrete hierarchical log-linear models
Annals of Statistics, 2009 In Bayesian analysis of multi-way contingency tables, the selection of a prior distribution for either the log-linear parameters or the cell probabilities parameters is a major challenge. In this paper, we define a flexible family of conjugate priors for
Dobra, Adrian +2 more
core +6 more sources
Graphical Local Genetic Algorithm for High-Dimensional Log-Linear Models
Mathematics, 2023 Graphical log-linear models are effective for representing complex structures that emerge from high-dimensional data. It is challenging to fit an appropriate model in the high-dimensional setting and many existing methods rely on a convenient class of ...
Lyndsay Roach, Xin Gao
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Restricted graphical log-linear models
Austrian Journal of Statistics, 2015 We introduce a new type of graphical log-linear model called restricted graphical log-linear model. This model is obtained by imposing equality restrictions on subsets of main effects and of first-order interactions.
Ricardo Ramírez-Aldana +1 more
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Log-mean linear models for binary data [PDF]
, 2012 This paper introduces a novel class of models for binary data, which we call log-mean linear models. The characterizing feature of these models is that they are specified by linear constraints on the log-mean linear parameter, defined as a log-linear ...
A. Roverato +4 more
core +3 more sources