On the Estimation of the Parameters of Markov Probability Models Using Macro Data
利用汇总数据估计马尔可夫概率模型参数
In this paper we consider the problem of estimating the parameters of a Markov model using so-called macro data. It will be shown that the stochastic process of the macro data is a Markov chain, which uniquely determines the probability structure of the underlying Markov model. A conditional least squares estimator exists under very weak conditions and this estimator is strongly consistent as time tends to infinity. Moreover this estimator is shown to be asymptotically…