We describe a procedure to introduce general dependence structures on a set of random variables. These include order-$q$ moving average-type structures, as well as seasonal, periodic, spatial and spatio-temporal dependences. The invariant marginal distribution can be in any family that is conjugate to an exponential family with quadratic variance function. Dependence is induced via a set of suitable latent variables whose conditional distribution mirrors the sampling distribution in a Bayesian conjugate analysis of such exponential families. We obtain strict stationarity as a special case.

翻译：我们描述了对一组随机变量采用一般依赖结构的程序,其中包括移动平均类型结构,以及季节性、周期性、空间性和时空依赖性,不固定的边际分布可能发生在与具有四分形功能的指数式家庭相融合的任何家庭中,通过一组合适的潜在变量诱发依赖性,这些变量的有条件分布反映了巴伊西亚州对此类指数式家庭的类似分析中的抽样分布。我们作为一个特例获得了严格的固定性。