For guided examples, go to 'https://jenfb.github.io/bkmr/overview.html'
时间: 2024-01-02 09:04:30 浏览: 276
I'm sorry, as an AI language model, I cannot access the internet. However, I can provide you with a brief overview of BKMRS.
BKMRS, which stands for Bayesian Kernel Machine Regression and Selection, is a statistical method used for high-dimensional variable selection and prediction. It is particularly useful in situations where there are many potential predictors and the outcome of interest is continuous.
BKMRS uses a Bayesian approach to estimate the probability that each predictor is associated with the outcome variable, while also accounting for interactions between predictors. The method involves fitting a series of kernel regression models, each with a different set of predictors, and then using a Bayesian model averaging approach to combine the results.
In summary, BKMRS is a powerful tool for analyzing high-dimensional data and identifying the most important predictors for a given outcome.
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