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A note on variable selection in nonparametric regression with dependent data

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  • González-Manteiga, Wenceslao
  • Quintela-del-Río, Alejandro
  • Vieu, Philippe

Abstract

We develop a nonparametric test, based on kernel smoothers, in order to decide whether some covariates could be suppressed in a multidimensional nonparametric regression study. We give the asymptotic distribution of the statistic involved in our test, under a general dependence assumption on the sample that allows for application to time series prediction.

Suggested Citation

  • González-Manteiga, Wenceslao & Quintela-del-Río, Alejandro & Vieu, Philippe, 2002. "A note on variable selection in nonparametric regression with dependent data," Statistics & Probability Letters, Elsevier, vol. 57(3), pages 259-268, April.
    • Handle: RePEc:eee:stapro:v:57:y:2002:i:3:p:259-268
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    References listed on IDEAS

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    1. Kozek, Andrzej S., 1991. "A nonparametric test of fit of a parametric model," Journal of Multivariate Analysis, Elsevier, vol. 37(1), pages 66-75, April.
    2. Bierens, Herman J, 1990. "A Consistent Conditional Moment Test of Functional Form," Econometrica, Econometric Society, vol. 58(6), pages 1443-1458, November.
    3. Lavergne, Pascal & Vuong, Quang H, 1996. "Nonparametric Selection of Regressors: The Nonnested Case," Econometrica, Econometric Society, vol. 64(1), pages 207-219, January.
    4. Hong, Yongmiao & White, Halbert, 1995. "Consistent Specification Testing via Nonparametric Series Regression," Econometrica, Econometric Society, vol. 63(5), pages 1133-1159, September.
    5. Horowitz, Joel L. & Härdle, Wolfgang, 1994. "Testing a Parametric Model Against a Semiparametric Alternative," Econometric Theory, Cambridge University Press, vol. 10(5), pages 821-848, December.
    6. Eustasio Barrio & Juan Cuesta-Albertos & Carlos Matrán & Sándor Csörgö & Carles Cuadras & Tertius Wet & Evarist Giné & Richard Lockhart & Axel Munk & Winfried Stute, 2000. "Contributions of empirical and quantile processes to the asymptotic theory of goodness-of-fit tests," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 9(1), pages 1-96, June.
    7. Fan, Yanqin & Li, Qi, 1996. "Consistent Model Specification Tests: Omitted Variables and Semiparametric Functional Forms," Econometrica, Econometric Society, vol. 64(4), pages 865-890, July.
    8. Hall, Peter, 1984. "Central limit theorem for integrated square error of multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, vol. 14(1), pages 1-16, February.
    9. Bierens, Herman J., 1982. "Consistent model specification tests," Journal of Econometrics, Elsevier, vol. 20(1), pages 105-134, October.
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    Cited by:

    1. Delsol, Laurent & Ferraty, Frédéric & Vieu, Philippe, 2011. "Structural test in regression on functional variables," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 422-447, March.
    2. Laurent Delsol, 2013. "No effect tests in regression on functional variable and some applications to spectrometric studies," Computational Statistics, Springer, vol. 28(4), pages 1775-1811, August.
    3. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    4. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    5. Debbarh, Mohammed & Viallon, Vivian, 2008. "Testing additivity in nonparametric regression under random censorship," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2584-2591, November.
    6. Avalos, Marta & Grandvalet, Yves & Ambroise, Christophe, 2007. "Parsimonious additive models," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2851-2870, March.

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