非线性模型滞后相依的广义互信息检验

Detecting Lags in Nonlinear Models Using General Mutual Information

中文关键词:  广义互信息  广义条件互信息  非线性时间序列  滞后相依.

英文关键词:general mutual information  general conditional mutual information  nonlinear time series  lag dependence.

中文摘要:

      用广义互信息和广义条件互信息度量非线性时间序列滞后相依.证明了这两个度量的性质,如变换不变性.统计量用关联积分估计,当独立的原假设成立时,估计量具有正态渐近分布.模拟结果表明,本文提出的方法能够检验出非线性时间序列的正确滞后相依.

英文摘要:

      The general mutual information (GMI) and general conditional mutual information (GCMI) are considered to measure lag dependences in nonlinear time series. Both of the measures have the property of invariance with transform. The statistics based on GMI and GCMI are estimated using the correlation integral. Under the hypothesis of independent series, the estimators have Gaussian asymptotic distributions. Simulations applied to generated nonlinear series demonstrate that the methods appear to find frequently the correct lags.