论文标题
Genmarkov：在R中对广义多元马尔可夫链进行建模
GenMarkov: Modeling Generalized Multivariate Markov Chains in R
论文作者
论文摘要
本文提出了对多元马尔可夫链（MMC）模型的新概括。马尔可夫链的未来值通常仅取决于以自回归方式的链的过去值。这项工作中提出的概括还考虑了可以确定性或随机性的外源变量。此外，在我们的模型中考虑了非均匀的马尔可夫链，考虑了MMC过去值的影响以及预定或外源的协变量的影响。蒙特卡洛模拟研究结果表明，我们的模型始终检测到非均匀的马尔可夫链。此外，经验例证通过在外源变量的空间状态上估算概率过渡矩阵，证明了这一新模型的相关性。这项工作的另一个又一个实用的贡献是开发了具有这种概括的新型R包装。
This article proposes a new generalization of the Multivariate Markov Chains (MMC) model. The future values of a Markov chain commonly depend on only the past values of the chain in an autoregressive fashion. The generalization proposed in this work also considers exogenous variables that can be deterministic or stochastic. Furthermore, the effects of the MMC's past values and the effects of pre--determined or exogenous covariates are considered in our model by considering a non--homogeneous Markov chain. The Monte Carlo simulation study findings showed that our model consistently detected a non--homogeneous Markov chain. Besides, an empirical illustration demonstrated the relevance of this new model by estimating probability transition matrices over the space state of the exogenous variable. An additional and practical contribution of this work is the development of a novel R package with this generalization.
