论文标题
拟合状态空间模型，用于长期预测非组织时间序列模型的对数模型
Fitting State-space Model for Long-term Prediction of the Log-likelihood of Nonstationary Time Series Models
论文作者
论文摘要
使用平方的长期预测误差评估了状态空间模型中长期预测的优点。为了估计适合长期预测的模型参数，我们设计了与长期预测误差差异相对应的修改对数可能性。趋势模型和带有和没有AR组件的季节性调整模型作为示例进行了检查。
The goodness of the long-term prediction in the state-space model was evaluated using the squared long-term prediction error. In order to estimate the model parameters suitable for long-term prediction, we devised a modified log-likelihood corresponding to the long-term prediction error variance. Trend models and seasonally adjusted models with and without AR component are examined as examples.
