Controlling randomness of results

Using the same dataset, multiple runs of CausalImpact produce different p-values and confidence intervals using bsts. They are within a small range of each other when using large niter values, but I want to produce the same values each time. How can these be controlled so that the results are consistent with every run?

Thanks