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Residual Empirical Processes and Weighted Sums for Time-Varying Processes with Applications to Testing for Homoscedasticity

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  • Gabe Chandler
  • Wolfgang Polonik

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  • Gabe Chandler & Wolfgang Polonik, 2017. "Residual Empirical Processes and Weighted Sums for Time-Varying Processes with Applications to Testing for Homoscedasticity," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(1), pages 72-98, January.
    • Handle: RePEc:bla:jtsera:v:38:y:2017:i:1:p:72-98
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    File URL: http://hdl.handle.net/10.1111/jtsa.12200
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    References listed on IDEAS

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    1. Winfried Stute, 2001. "Residual analysis for ARCH(p)-time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 10(2), pages 393-403, December.
    2. Anton Schick & Wolfgang Wefelmeyer, 2002. "Estimating the Innovation Distribution in Nonlinear Autoregressive Models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 54(2), pages 245-260, June.
    3. Paparoditis, Efstathios, 2010. "Validating Stationarity Assumptions in Time Series Analysis by Rolling Local Periodograms," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 839-851.
    4. Orbe, Susan & Ferreira, Eva & Rodriguez-Poo, Juan, 2005. "Nonparametric estimation of time varying parameters under shape restrictions," Journal of Econometrics, Elsevier, vol. 126(1), pages 53-77, May.
    5. W. Wefelmeyer, 1994. "An efficient estimator for the expectation of a bounded function under the residual distribution of an autoregressive process," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(2), pages 309-315, June.
    6. Fryzlewicz, Piotr & Sapatinas, Theofanis & Subba Rao, Suhasini, 2006. "A Haar-Fisz technique for locally stationary volatility estimation," LSE Research Online Documents on Economics 25225, London School of Economics and Political Science, LSE Library.
    7. Dahlhaus, Rainer & Neumann, Michael H., 2001. "Locally adaptive fitting of semiparametric models to nonstationary time series," Stochastic Processes and their Applications, Elsevier, vol. 91(2), pages 277-308, February.
    8. Ingrid Keilegom & Wenceslao González Manteiga & César Sánchez Sellero, 2008. "Goodness-of-fit tests in parametric regression based on the estimation of the error distribution," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(2), pages 401-415, August.
    9. Chandler, Gabriel & Polonik, Wolfgang, 2006. "Discrimination of Locally Stationary Time Series Based on the Excess Mass Functional," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 240-253, March.
    10. Neumeyer, Natalie & Van Keilegom, Ingrid, 2010. "Estimating the error distribution in nonparametric multiple regression with applications to model testing," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1067-1078, May.
    11. Ruprecht Puchstein & Philip Preuß, 2016. "Testing for Stationarity in Multivariate Locally Stationary Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(1), pages 3-29, January.
    12. Michael G. Akritas & Ingrid Van Keilegom, 2001. "Non‐parametric Estimation of the Residual Distribution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(3), pages 549-567, September.
    13. Gabriel Chandler & Wolfgang Polonik, 2012. "Mode Identification of Volatility in Time-Varying Autoregression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(499), pages 1217-1229, September.
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