Results 11 to 20 of about 3,443,781 (274)
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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LinDA: linear models for differential abundance analysis of microbiome compositional data [PDF]
Genome Biology, 2021 Differential abundance analysis is at the core of statistical analysis of microbiome data. The compositional nature of microbiome sequencing data makes false positive control challenging. Here, we show that the compositional effects can be addressed by a
Huijuan Zhou +3 more
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A Scheme for Molecular Computation of Maximum Likelihood Estimators for Log-Linear Models [PDF]
DNA, 2015 We propose a novel molecular computing scheme for statistical inference. We focus on the much-studied statistical inference problem of computing maximum likelihood estimators for log-linear models.
Manoj Gopalkrishnan
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Log-linear Combinations of Monolingual and Bilingual Neural Machine Translation Models for Automatic Post-Editing [PDF]
Conference on Machine Translation, 2016 This paper describes the submission of the AMU (Adam Mickiewicz University) team to the Automatic Post-Editing (APE) task of WMT 2016. We explore the application of neural translation models to the APE problem and achieve good results by treating ...
Marcin Junczys-Dowmunt +1 more
semanticscholar +1 more source
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
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DISCRETE MULTIVARIATE ANALYSIS USING LOG - LINEAR MODELS
Ecosistemas y Recursos Agropecuarios, 2014 a procedure is definid for obtaining maximun likelihood estimates for the parameters of a family of log - linear models which includes the general log - linear model, logit models, multinominal logit models, and association models as well as models for ...
Robert J. Flowers
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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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Revista de Saúde Pública, 1998 OBJETIVO: Complementar dados de investigação anterior sobre o risco de indução de câncer devido à ingestão de 226Ra, 228Ra e 222Rn em fontes de águas minerais de uma região de altos níveis de radioatividade natural, do Brasil.
Eduardo Freitas da Silva +1 more
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Computation, 2022 Over the past decade, a series of procedures has been introduced to estimate, using a non-iterative method, the linear-by-linear association parameter of an ordinal log-linear model.
Sidra Zafar +3 more
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