论文标题
在可变块上的结构时间序列语法
Structural time series grammar over variable blocks
论文作者
论文摘要
结构性时间序列模型可加上分解为生成的，语义上的组件，每个组件都取决于参数的向量。我们证明，将每个生成分量及其参数向量作为单个潜在的结构时间序列节点可以简化有关结构时间序列组件的集合的推理。然后，我们引入了关于结构时间序列节点和参数向量的形式语法。语法中的有效句子可以解释为生成结构时间序列模型。语法的扩展还可以表达包括更改点的结构时间序列模型，尽管这些模型一定不是生成性的。我们证明了该语法产生的语言的初步实施。我们讨论了可能的未来工作。
A structural time series model additively decomposes into generative, semantically-meaningful components, each of which depends on a vector of parameters. We demonstrate that considering each generative component together with its vector of parameters as a single latent structural time series node can simplify reasoning about collections of structural time series components. We then introduce a formal grammar over structural time series nodes and parameter vectors. Valid sentences in the grammar can be interpreted as generative structural time series models. An extension of the grammar can also express structural time series models that include changepoints, though these models are necessarily not generative. We demonstrate a preliminary implementation of the language generated by this grammar. We close with a discussion of possible future work.
