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    题名: 相依資料的條件獨立檢定
    A conditional independence test for dependent data
    作者: 鄭宇翔
    Cheng, Yu Hsiang
    贡献者: 黃子銘
    Huang, Tzee Ming
    鄭宇翔
    Cheng, Yu Hsiang
    关键词: 條件獨立檢定
    日期: 2012
    上传时间: 2013-09-02 15:35:46 (UTC+8)
    摘要: 在一個考慮多個變數的問題中，變數間是否為條件獨立常是人們關心的議題。Huang[10]曾提出一個適用於IID資料的條件獨立檢定方法，此論文將說明此統計量亦適用於alpha-mixing資料的條件獨立檢定問題。另外本論文亦將考慮當條件變數為離散時的條件獨立檢定。本文證實藉由適當修正Huang的檢定統計量，則可解決上述資料型態的條件獨立檢定問題，另外文中亦會提供此修正統計量在條件獨立下的收斂性質。最後我們將利用模擬研究及實際資料分析來說明上述方法的表現。
    參考文獻: [1] Patrick Billingsley. Probability and Measure. John Wiley & Sons, New York, 1995.

    [2] Taou.k Bouezmarni, Jeroen V. K. Rombouts, and Abderrahim Taamouti. A nonparametric copula based test for conditional independence with applications to Granger causality. Working papers, Departamento de Economia Universidad Carlos III de Madrid, 2009.

    [3] Yu-Hsiang Cheng and Tzee-Ming Huang. A conditional independence test for dependent data based on maximal conditional correlation. Journal of Multivariate Analysis, 107:210–226, 2012.

    [4] Jacques Dauxois and Guy Martial Nkiet. Nonlinear canonical analysis and independence tests. The Annals of Statistics, 26(4):1254–1278, 1998.

    [5] David L. Banks (ed.), Campbell B. Read (ed.), and Samuel Kotz (ed.). Encyclopedia of Statistical Sciences (9 Vols. Plus Supplement), Volume S. John Wiley & Sons, 1989.

    [6] Stephen E. Fienberg. The Analysis of Cross-classified Categorical Data. MIT Press, 1980.

    [7] J. P. Florens and Denis Fougere. Noncausality in continuous time. Econometrica, 64(5):1195–1212, 1996.

    [8] J. P. Florens and M. Mouchart. A note on noncausality. Econometrica, 50(3):583–591, 1982.

    [9] Harold Hotelling. Relations between two sets of variates. Biometrika, 28:321– 377, 1936.

    [10] Tzee-Ming Huang. Testing conditional independence using maximal nonlinear conditional correlation. The Annals of Statistics, 38(4):2047–2091, 2010.

    [11] Anant M. Kshirsagar. Multivariate Analysis. Marcel Dekker, Inc., New York, 1972.

    [12] Lexin Li, R. Dennis Cook, and Christopher J. Nachtsheim. Model-free variable selection. Journal of the Royal Statistical Society, Series B: Statistical Methodology, 67(2):285–299, 2005.

    [13] Oliver Bruce Linton and Pedro Gozalo. Conditional independence restrictions: Testing and estimation. Cowles Foundation Discussion Papers 1140, Cowles Foundation, Yale University, 1996.

    [14] Roger B. Nelsen. An Introduction to Copulas. Springer, New York, 2006.

    [15] Efstathios Paparoditis and Dimitris N. Politis. The local bootstrap for kernel estimators under general dependence conditions. Annals of the Institute of Statistical Mathematics, 52(1):139–159, 2000.

    [16] Karl Pearson. On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical
    Magazine Series 5, 50(302):157–175, 1900.

    [17] Larry L. Schumaker. Spline Functions: Basic Theory. Wiley-Interscience, New York, 1981.

    [18] Liangjun Su and Halbert White. A consistent characteristic function-based test for conditional
    independence. Journal of Econometrics, 141:807-834, 2007.

    [19] Liangjun Su and Halbert White. A nonparametric Hellinger metric test for conditional independence.
    Econometric Theory, 24(4):829–864, 2008.

    [20] S. S. Wilks. Certain generalizations in the analysis of variance. Biometrika, 24:471–494, 1932.
    描述: 博士
    國立政治大學
    統計研究所
    96354501
    101
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0096354501
    数据类型: thesis
    显示于类别:[統計學系] 學位論文

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