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A General Approach to Derive Chi-Square Type of Goodness-of-Fit Tests for Lifetime Data

In: Lifetime Data: Models in Reliability and Survival Analysis

Author

Listed:
  • Sam Hawala

    (University of St. Thomas, Department of Mathematics)

  • Jane-Ling Wang

    (University of California, Division of Statistics)

Abstract

Pearson’s original chi-square test for goodness-of-fit has been extended and generalized in various ways to test the composite hypothesis of a certain parametric family {F (x; θ): θ ∈ Θ}. We illustrate in this paper that, for lifetime data that are subject to incomplete observation, a unified approach is available to derive general chi-square tests for parametric families, regardless of the sampling plan for such incomplete data. Let % feaagCart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn % hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr % 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9 % vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x % fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaCbiaeaaca % WGgbaaleqabaGaey4jIKnaaOWaaSbaaSqaaiaad6gaaeqaaaaa!39DF!]]

Suggested Citation

  • Sam Hawala & Jane-Ling Wang, 1996. "A General Approach to Derive Chi-Square Type of Goodness-of-Fit Tests for Lifetime Data," Springer Books, in: Nicholas P. Jewell & Alan C. Kimber & Mei-Ling Ting Lee & G. A. Whitmore (ed.), Lifetime Data: Models in Reliability and Survival Analysis, pages 113-123, Springer.
  • Handle: RePEc:spr:sprchp:978-1-4757-5654-8_17
    DOI: 10.1007/978-1-4757-5654-8_17
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