Abstract
In order to solve the problem of large mean square error of regression coefficient in traditional Bayesian high-dimensional data analysis, sir model program is applied to realize Bayesian high dimensional data analysis. This paper capture Bayesian high dimensional data, and use sir model program to set super parameters. The prior probability of Bayesian high dimensional data analysis is calculated, and the topological structure of Bayesian high dimensional data analysis is constructed to realize Bayesian high dimensional data analysis. The results show that the mean square error of regression coefficient in the experimental group is significantly lower than that in the control group, which can solve the problem of large mean square error in traditional analysis.
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