Fitting nonlinear time-series models with applications to stochastic variance models
非线性时间序列模型的拟合及随机方差模型应用
New strategies for the implementation of maximum likelihood estimation of nonlinear time series models are suggested. They make use of recent work on the EM algorithm and iterative simulation techniques. The estimation procedures are applied to the problem of fitting stochastic variance models to exchange rate data.