Search results for " penalized inference"

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Inferring slowly-changing dynamic gene-regulatory networks

2015

Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experi…

Dynamic network analysisL1 penalized inferenceComputer scienceT-LymphocytesGene regulatory networkgene regulatory networkMachine learningcomputer.software_genreBiochemistrygene-regulatory networksStructural Biologygraphical modelscomputer simulationT lymphocyteHumansGene Regulatory NetworkshumanGraphical modelMolecular Biologylymphocyte activationClass (computer programming)Models Statisticalalgorithmbusiness.industryResearchApplied Mathematicsstatistical modelStatistical modelComplex networkQuantitative Biology::GenomicsComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONConditional independencemicroarray analysisComputingMethodologies_GENERALArtificial intelligencebusinessmetabolismRandom variablecomputerAlgorithmsBMC Bioinformatics
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A Software Tool For Sparse Estimation Of A General Class Of High-dimensional GLMs

2022

Generalized linear models are the workhorse of many inferential problems. Also in the modern era with high-dimensional settings, such models have been proven to be effective exploratory tools. Most attention has been paid to Gaussian, binomial and Poisson settings, which have efficient computational implementations and where either the dispersion parameter is largely irrelevant or absent. However, general GLMs have dispersion parameters φ that affect the value of the log- likelihood. This in turn, affects the value of various information criteria such as AIC and BIC, and has a considerable impact on the computation and selection of the optimal model.The R-package dglars is one of the standa…

Statistics and ProbabilityNumerical Analysishigh-dimensional data dglars penalized inference computational statisticsStatistics Probability and UncertaintySettore SECS-S/01 - Statistica
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