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Nonparametric tests for multiple regression under progressive censoring

Author

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  • Majumdar, Hiranmay
  • Sen, Pranab Kumar

Abstract

For continuous observations from time-sequential studies, suitable Cramér-von Mises and Kolmogorov-Smirnov types of (nonparametric) statistics (based on linear rank statistics) for testing hypotheses on some multiple-regression models are proposed and studied. The asymptotic theory of these tests is provided for both the null and (local) alternative hypotheses situations and is based on the weak convergence of suitable rank order processes (on the D[0, 1] space) to certain functions of Brownian motions. Bahadur efficiency results are also presented. Empirical values of the percentile points of the null distributions of the proposed test statistics, obtained through simulation studies, are also provided.

Suggested Citation

  • Majumdar, Hiranmay & Sen, Pranab Kumar, 1978. "Nonparametric tests for multiple regression under progressive censoring," Journal of Multivariate Analysis, Elsevier, vol. 8(1), pages 73-95, March.
    • Handle: RePEc:eee:jmvana:v:8:y:1978:i:1:p:73-95
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    Cited by:

    1. N. Balakrishnan & Donghoon Han & G. Iliopoulos, 2011. "Exact inference for progressively Type-I censored exponential failure data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(3), pages 335-358, May.
    2. Gopaldeb Chattopadhyay & Indranil Mukhopadhyay, 2010. "Progressive censoring under inverse sampling for nonparametric multi-sample location problem," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(2), pages 325-341, August.

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