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

Sam Hawala and Jane-Ling Wang
Additional contact information
Sam Hawala: University of St. Thomas, Department of Mathematics
Jane-Ling Wang: University of California, Division of Statistics

A chapter in Lifetime Data: Models in Reliability and Survival Analysis, 1996, pp 113-123 from Springer

Abstract: 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!]]

Keywords: Sampling Plan; Null Distribution; Generalize Inverse; Lifetime Data; Composite Hypothesis (search for similar items in EconPapers)
Date: 1996
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4757-5654-8_17

Ordering information: This item can be ordered from
http://www.springer.com/9781475756548

DOI: 10.1007/978-1-4757-5654-8_17

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().