加权马尔可夫模型在企业景气指数预测中的应用

Application of Weighted Markov Model in Forecasting Enterprise Prosperity Index

企业景气指数作为随机的变量,在每个季度统计过程中会存在着比较大的不确定性和不精确性的特点。文章以北京市1999—2013年共60个季度企业景气指数的数据资料作为实例,结合加权马尔可夫数学模型进行具体的应用。论证该模型在给定提供的时间序列中的实践效果,最后获得的结果与实际情况基本吻合,为以后对企业景气指数的预测提供新的研究方法和预测依据。

As a random variable, the enterprise prosperity index has greater uncertainty and inaccuracy in each quarterly sta- tistics. This paper takes the numerical data of Beijng＇ s enterprise prosperity index of 60 quarters from 1999 to 2013 as an empiri- cal sample, and combines with Markov mathematical model to conduct a specific application. The paper also expounds and proves the practical effect of the model in the given time sequence, Ultimately, the paper obtains an outcome approximately consistent with the actual situation, thus providing a new research method and forecast basis for future prediction of enterprise prosperity index.