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Approximate and Asymptotic Distributions of Chi-Squared-Type Mixtures With Applications

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  • Jin-Ting Zhang

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  • Jin-Ting Zhang, 2005. "Approximate and Asymptotic Distributions of Chi-Squared-Type Mixtures With Applications," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 273-285, March.
    • Handle: RePEc:bes:jnlasa:v:100:y:2005:p:273-285
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    Cited by:

    1. Zhang, Jin-Ting & Guo, Jia & Zhou, Bu, 2017. "Linear hypothesis testing in high-dimensional one-way MANOVA," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 200-216.
    2. Tianming Zhu & Jin-Ting Zhang, 2022. "Linear hypothesis testing in high-dimensional one-way MANOVA: a new normal reference approach," Computational Statistics, Springer, vol. 37(1), pages 1-27, March.
    3. Mingxiang Cao & Ziyang Cheng & Kai Xu & Daojiang He, 2024. "A scale-invariant test for linear hypothesis of means in high dimensions," Statistical Papers, Springer, vol. 65(6), pages 3477-3497, August.
    4. Zhang, Jin-Ting & Zhu, Tianming, 2022. "A new normal reference test for linear hypothesis testing in high-dimensional heteroscedastic one-way MANOVA," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    5. Zhang, Jin-Ting & Zhu, Tianming, 2024. "A fast and accurate kernel-based independence test with applications to high-dimensional and functional data," Journal of Multivariate Analysis, Elsevier, vol. 202(C).
    6. Huang, Zhendong & Ferrari, Davide & Qian, Guoqi, 2017. "Parsimonious and powerful composite likelihood testing for group difference and genotype–phenotype association," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 37-49.
    7. Katarzyna Bech & Grant Hillier, 2015. "Nonparametric testing for exogeneity with discrete regressors and instruments," CeMMAP working papers CWP11/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Jin-Ting Zhang & Xuehua Liang, 2014. "One-Way anova for Functional Data via Globalizing the Pointwise F-test," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 51-71, March.
    9. Zhang, Jin-Ting & Zhou, Bu & Guo, Jia, 2022. "Linear hypothesis testing in high-dimensional heteroscedastic one-way MANOVA: A normal reference L2-norm based test," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
    10. Zhang, Jin-Ting & Guo, Jia & Zhou, Bu, 2024. "Testing equality of several distributions in separable metric spaces: A maximum mean discrepancy based approach," Journal of Econometrics, Elsevier, vol. 239(2).
    11. Tianming Zhu & Pengfei Wang & Jin-Ting Zhang, 2024. "Two-sample Behrens–Fisher problems for high-dimensional data: a normal reference F-type test," Computational Statistics, Springer, vol. 39(6), pages 3207-3230, September.
    12. Fang Han & Wei Pan, 2012. "A Composite Likelihood Approach to Latent Multivariate Gaussian Modeling of SNP Data with Application to Genetic Association Testing," Biometrics, The International Biometric Society, vol. 68(1), pages 307-315, March.
    13. Zhang, Liang & Zhu, Tianming & Zhang, Jin-Ting, 2020. "A Simple Scale-Invariant Two-Sample Test for High-dimensional Data," Econometrics and Statistics, Elsevier, vol. 14(C), pages 131-144.
    14. Mariusz Kubkowski & Jan Mielniczuk, 2021. "Asymptotic Distributions of Empirical Interaction Information," Methodology and Computing in Applied Probability, Springer, vol. 23(1), pages 291-315, March.
    15. Jin-Ting Zhang & Bu Zhou & Jia Guo, 2022. "Testing high-dimensional mean vector with applications," Statistical Papers, Springer, vol. 63(4), pages 1105-1137, August.
    16. Huang, Peng & Gu, Yingkui & Li, He & Yazdi, Mohammad & Qiu, Guangqi, 2023. "An Optimal Tolerance Design Approach of Robot Manipulators for Positioning Accuracy Reliability," Reliability Engineering and System Safety, Elsevier, vol. 237(C).

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