Download e-book for kindle: A Nonlinear Time Series Workshop: A Toolkit for Detecting by Douglas M. Patterson

By Douglas M. Patterson

ISBN-10: 144198688X

ISBN-13: 9781441986887

ISBN-10: 1461346657

ISBN-13: 9781461346654

The advanced dynamic habit exhibited through many nonlinear platforms - chaos, episodic volatility bursts, stochastic regimes switching - has attracted a great deal of recognition lately. A Nonlinear Time sequence Workshop offers the reader with either the statistical history and the software program instruments invaluable for detecting nonlinear habit in time sequence info. the main worthwhile present detection ideas are defined, together with Engle's LaGrange Multiplier try out for conditional hetero-skedasticity and exams in accordance with the correlation size and at the expected bispectrum. those ideas are illustrated utilizing real facts from fields akin to economics, finance, engineering, and geophysics.

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Additional info for A Nonlinear Time Series Workshop: A Toolkit for Detecting and Identifying Nonlinear Serial Dependence

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The Hinich bispectral test has the nice property that it is unaffected by the application of a linear filter to Yt. This follows from the fact that the squared skewness function, tpz (f},fz), is invariant to linear filtering: Theorem 2-2 If {Yt} satisfies the assumptions of Theorem 2-1 and Z. , fz). Proof of Theorem 2-2: This is proven in Ashley, Patterson, and Hinich (1986, p. +fz]}) appears in both the numerator and denominator oftp~(f}, fz) and hence cancels out. Ashley and Patterson 45 Consequently - in contrast to all the other tests - the Hinich bispectral test is not confounded by linear serial dependence remaining in the data due to imperfect prewhitening.

Yournal ofthe Royal Statistical Society B 54, 399-426 . 8. " Journal ofthe Royal Statistical Society B 31, 350-371 . , C. L. Sayers and P. " 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.

Line 8: Control line for the Bicovariance test. It is filled out the same as line 7. line 9: Control line for the McLeod-Li test. It is filled out the same as line 7. 58 A Nonlinear Time Series Workshop line 10: Control line for the Engle LM test. The first itemon this line must be a lower class "y" to specify that the test will be done, or a lower case "n" to specify that the test not be done. The next item is an integer specifying how many lags to use in the test. A typical value would be 5; the maximum allowed value is 50.

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A Nonlinear Time Series Workshop: A Toolkit for Detecting and Identifying Nonlinear Serial Dependence by Douglas M. Patterson


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