We suggest how to construct joint confidence distributions for several parameters and apply these ideas to an autoregressive process of general order. The implied non informative prior for the parameters, i.e. the ratio between the confidence density and the likelihood function, is proved to be asymptotically flat in the stationary case. However, in the presence of a unit root, the implied prior needs to be adjusted. The results are illustrated by simulation studies and empirical examples.

翻译：本文提出如何构建多个参数的联合置信分布，并将这些思想应用于一般阶数的自回归过程。在平稳情形下，证明了参数所隐含的无信息先验（即置信密度与似然函数之比）具有渐近平坦性。然而，当存在单位根时，需要对隐含先验进行调整。通过模拟研究和实证案例对结果进行了说明。