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SOME RECENT DEVELOPMENTS IN NONLINEAR TIME-SERIES MODELING, TESTING, AND FORECASTING
被引:114
|作者:
DEGOOIJER, JG
KUMAR, K
机构:
[1] UMEA UNIV, DEPT STAT, S-90187 UMEA, SWEDEN
[2] NATL UNIV SINGAPORE, DEPT ECON & STAT, SINGAPORE 0511, SINGAPORE
[3] MONASH UNIV, DEPT ECONOMETR, CLAYTON, VIC 3168, AUSTRALIA
关键词:
ARCH;
BILINEAR;
CUSUMS;
EXPONENTIAL AR;
IDENTIFICATION;
INVERTIBILITY;
LAGRANGE-MULTIPLIER TEST;
MULTISTEP-AHEAD FORECASTING;
ORDER SELECTION;
THRESHOLD MODEL;
D O I:
10.1016/0169-2070(92)90115-P
中图分类号:
F [经济];
学科分类号:
02 ;
摘要:
Most of the recent work in time series analysis has been done on the assumption that the structure of the series can be described by linear time series models. However, there are occasions when subject-matter, theory or data suggest that linear models are unsatisfactory. In those cases it is desirable to look at non-linear alternatives. This paper gives an overview of the most recent developments in this area. Particular attention is paid to the strengths and weaknesses (advantages and disadvantages) of a large number of models and tests for non-linearity, focusing on 'ready-to-use' issues rather than discussing technical details. Various problems in forecasting from non-linear models are discussed. Some guidelines for practical non-linear time series modelling and forecasting are also included.
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页码:135 / 156
页数:22
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