کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9732517 | 1481479 | 2005 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detecting nonlinearity in time series by model selection criteria
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
مدیریت، کسب و کار و حسابداری
کسب و کار و مدیریت بین المللی
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چکیده انگلیسی
This article analyzes the use of model selection criteria for detecting nonlinearity in the residuals of a linear model. Model selection criteria are applied for finding the order of the best autoregressive model fitted to the squared residuals of the linear model. If the order selected is not zero, this is considered as an indication of nonlinear behavior. The BIC and AIC criteria are compared to some popular nonlinearity tests in three Monte Carlo experiments. We conclude that the BIC model selection criterion seems to offer a promising tool for detecting nonlinearity in time series. An example is shown to illustrate the performance of the tests considered and the relationship between nonlinearity and structural changes in time series.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Forecasting - Volume 21, Issue 4, OctoberâDecember 2005, Pages 731-748
Journal: International Journal of Forecasting - Volume 21, Issue 4, OctoberâDecember 2005, Pages 731-748
نویسندگان
Daniel Peña, Julio Rodriguez,