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Using the Autodependogram in Model Diagnostic Checking

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Part of the book series: Studies in Theoretical and Applied Statistics ((STASSPSS))

Abstract

In this chapter the autodependogram is contextualized in model diagnostic checking for nonlinear models by studying the lag-dependencies of the residuals. Simulations are considered to evaluate its effectiveness in this context. An application to the Swiss Market Index is also provided.

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References

  1. Bagnato, L.: Nonparametric ARCH with additive mean and multiplicative volatility: A new estimation procedure. Statistica & Applicazioni VII(1), 63–76 (2009)

    Google Scholar 

  2. Bagnato, L., Punzo, A.: On the use of χ 2-test to check serial independence. Statistica & Applicazioni VIII(1), 57–74 (2010)

    Google Scholar 

  3. Bagnato, L., Punzo, A.: Checking serial independence of residuals from a nonlinear model. In: Gaul, W., Geyer-shulz, A., Schmidt-thieme, L., Kunze, J. (eds.) Challenges at the Interface of Data Analysis, Computer Science, and Optimization, Studies in Classification, Data Analysis and Knowledge Organization, pp. 203–211. Springer, Berlin-Heidelberg (2012)

    Chapter  Google Scholar 

  4. Bagnato, L., Punzo, A., Nicolis, O.: The autodependogram: a graphical device to investigate serial dependences. J. Time Anal. 33(2), 233–254 (2012)

    Article  MathSciNet  Google Scholar 

  5. Cochran, W.G.: Some methods for strengthening the common χ 2 tests. Biometrics 10(4), 417–451 (1954)

    Article  MathSciNet  MATH  Google Scholar 

  6. Jianqing, F., Qiwei, Y.: Nonlinear Time Series: Nonparametric and Parametric Methods. Springer, New York (2003)

    MATH  Google Scholar 

  7. Mann, H.B., Wald, A.: On the choice of the number of intervals in the application of the chi-square test. Ann. Math. Stat. 13(3), 306–317 (1942)

    Article  MathSciNet  MATH  Google Scholar 

  8. R Development Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna (2011). ISBN 3-900051-07-0

    Google Scholar 

  9. Yang, L., Härdle, W., Nielsen, J.P.: Nonparametric autoregression with multiplicative volatility and additive mean. J. Time Anal. 20(5), 579–604 (1999)

    Article  MATH  Google Scholar 

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Correspondence to Luca Bagnato .

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Bagnato, L., Punzo, A. (2013). Using the Autodependogram in Model Diagnostic Checking. In: Torelli, N., Pesarin, F., Bar-Hen, A. (eds) Advances in Theoretical and Applied Statistics. Studies in Theoretical and Applied Statistics(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35588-2_13

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