GENERALIZED INTEGER-VALUED AUTOREGRESSION
将整数值AR1模型推广到更符合经济计数数据特征的情形，虽失去精确分布性质，但可通过矩条件进行估计、检验和预测，并用工业部门企业数量数据示例。
The integer-valued AR1 model is generalized to encompass some of the more likely features of economic time series of count data. The generalizations come at the price of loosing exact distributional properties. For most specifications the first and second order both conditional and unconditional moments can be obtained. Hence estimation, testing and forecasting are feasible and can be based on least squares or GMM techniques. An illustration based on the number of plants within an industrial sector is considered.