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Posterior mean Bayesian lasso estimates (computed over a grid of λ values, using 10,000 samples after burn-in) and corresponding 95% credible intervals (equal-tailed) of Diabetes data (n = 442) covariates. The hyperprior parameters were chosen as a = 1, b = 0.1. OLS estimates with corresponding 95% confidence intervals are also reported. For the lasso estimates, the tuning parameter was chosen by 10-fold CV of the LARS algorithm.
