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Testing the equality of linear single-index models

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  • Lin, Wei
  • Kulasekera, K.B.

Abstract

Comparison of nonparametric regression models has been extensively discussed in the literature for the one-dimensional covariate case. The comparison problem largely remains open for completely nonparametric models with multi-dimensional covariates. We address this issue under the assumption that models are single-index models (SIMs). We propose a test for checking the equality of the mean functions of two (or more) SIM's. The asymptotic normality of the test statistic is established and an empirical study is conducted to evaluate the finite-sample performance of the proposed procedure.

Suggested Citation

  • Lin, Wei & Kulasekera, K.B., 2010. "Testing the equality of linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1156-1167, May.
    • Handle: RePEc:eee:jmvana:v:101:y:2010:i:5:p:1156-1167
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    References listed on IDEAS

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    Cited by:

    1. Wai-Yin Poon & Hai-Bin Wang, 2014. "Multivariate partially linear single-index models: Bayesian analysis," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 755-768, December.
    2. Jun Zhang & Zhenghui Feng & Xiaoguang Wang, 2018. "A constructive hypothesis test for the single-index models with two groups," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(5), pages 1077-1114, October.
    3. David Pejčoch, 2014. "CADAQUES: The Methodology for Complex Data and Information Management [CADAQUES: Metodika pro komplexní řízení kvality dat a informací]," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2014(1), pages 44-56.
    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.

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