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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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