Название: Handbook of Bayesian Variable Selection
Автор: Mahlet G. Tadesse, Marina Vannucci
Издательство: Chapman and Hall/CRC
Серия: Handbooks of Modern Statistical Methods
Год: 2022
Страниц: 491
Язык: английский
Формат: pdf (true)
Размер: 53.1 MB
Bayesian variable selection has experienced substantial developments over the past 30 years with the proliferation of large data sets. Identifying relevant variables to include in a model allows simpler interpretation, avoids overfitting and multicollinearity, and can provide insights into the mechanisms underlying an observed phenomenon. Variable selection is especially important when the number of potential predictors is substantially larger than the sample size and sparsity can reasonably be assumed. The Handbook of Bayesian Variable Selection provides a comprehensive review of theoretical, methodological and computational aspects of Bayesian methods for variable selection.
Автор: Mahlet G. Tadesse, Marina Vannucci
Издательство: Chapman and Hall/CRC
Серия: Handbooks of Modern Statistical Methods
Год: 2022
Страниц: 491
Язык: английский
Формат: pdf (true)
Размер: 53.1 MB
Bayesian variable selection has experienced substantial developments over the past 30 years with the proliferation of large data sets. Identifying relevant variables to include in a model allows simpler interpretation, avoids overfitting and multicollinearity, and can provide insights into the mechanisms underlying an observed phenomenon. Variable selection is especially important when the number of potential predictors is substantially larger than the sample size and sparsity can reasonably be assumed. The Handbook of Bayesian Variable Selection provides a comprehensive review of theoretical, methodological and computational aspects of Bayesian methods for variable selection.