【摘要】 首先,用条件最小二乘方法讨论缺失数据下MGINAR(p)模型的参数估计问题,得到了参数的条件最小二乘估计.其次,模拟验证4种处理缺失数据方法的可行性并比较估计效果,模拟结果表明:当缺失概率较小时,可使用个案剔除法或均值插补法;当缺失概率较大时,可使用桥插补法,以降低估计偏差.更多还原

【Abstract】 Firstly, by using the method of conditional least squares, we discussed the problem of parameter estimation for MGINAR(p) model with missing data, and obtained the conditional least square estimations of parameters. Secondly, numerical simulation was used to verify the feasibility of four methods for processing missing data and to compare the estimation effects. The simulation results show that when the missing probability is small, the case rejection method or the mean value interpolation method can be used, and when the missing probability is large, the bridge interpolation method can be used to reduce the estimation bias.更多还原