## Abstract Forecasting for nonlinear time series is an important topic in time series analysis. Existing numerical algorithms for multiβstepβahead forecasting ignore accuracy checking, alternative Monte Carlo methods are also computationally very demanding and their accuracy is difficult to contro
A Score Type Test for General Autoregressive Models in Time Series
β Scribed by Jian-hong Wu; Li-xing Zhu
- Publisher
- Institute of Applied Mathematics, Chinese Academy of Sciences and Chinese Mathematical Society
- Year
- 2007
- Tongue
- English
- Weight
- 183 KB
- Volume
- 23
- Category
- Article
- ISSN
- 0168-9673
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In this paper we propose a new test of conditional heteroskedasticity for time series by introducing a Kolmogorov-Smirnov-type test statistic. The asymptotic properties of the new test statistic are established. The results demonstrate that such a test is consistent.