By Douglas M. Patterson
The complicated dynamic habit exhibited by way of many nonlinear platforms - chaos, episodic volatility bursts, stochastic regimes switching - has attracted a great deal of recognition in recent times. A Nonlinear Time sequence Workshop offers the reader with either the statistical historical past and the software program instruments priceless for detecting nonlinear habit in time sequence information. the main priceless present detection thoughts are defined, together with Engle's LaGrange Multiplier attempt for conditional hetero-skedasticity and checks according to the correlation measurement and at the expected bispectrum. those concepts are illustrated utilizing genuine info from fields similar to economics, finance, engineering, and geophysics.
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Extra info for A Nonlinear Time Series Workshop: A Toolkit for Detecting and Identifying Nonlinear Serial Dependence
All of these are self explanatory, with the possible exception of C(6), which is the sample sixth-order cumulant of the data. Figure 3-3 displays the last of the prewhitening models estimated and the actual selected prewhitening model. In the Figure , an AR(l) model was chosen because it minimized the Schwartz criterion for model selection. Next the output file lists results on each test. The results labeled, "asymptotic theory" are based on the large sample distributions of the relevant test statistics, discussed in Chapter 2.
O. * McLeod-Li test y 5 0000 O. O. O. O. y 5 0 0 0 0 O. O. O. O. 7) * Engle LM test * Tsay test * start record-end record 0 means last rec Save the control file and exit the text editor or word processor. If you use a word processor, be sure the file is saved as an ASCII or text file. 3. exe" in the Windows Explorer file listing or open a DOS box in Windows, go to the directory where the program is located, and type "toolkit" at a DOS prompt. ) 4. out, is too large to be easily displayed in a single figure .
International Economic Review 31,9911020. Subba Rao, T. and Gabr, M. (1980) "A Test for Linearity of Stationary Time Series Analysis"Journal of Time Series Analys is 1, 145-58. Tsay, Ruey S. (1986) "Nonlinearity Tests for Time Series" Biometrika 73. 461-6 . White, H. " Journal ofthe American Statistical Association 84,1003-1013 . It is obviously infeasible to include every known test in the Toolkit. Omitted tests include : Ramsey (1969) , Ashley and Patterson (1986), Mizraeh (1991) , Nychka, et al.
A Nonlinear Time Series Workshop: A Toolkit for Detecting and Identifying Nonlinear Serial Dependence by Douglas M. Patterson
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