Goodness of fit tests under random censorship

Graduate Thesis Or Dissertation

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Citeable URL: https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/x059cb54z

Descriptions

Attribute Name	Values
Creator	Chen, Jiin-chiang
Abstract	The classical chi-square goodness of fit test and the Neyman smooth tests are generalized for arbitrarily right-censored samples. The test statistics are shown to have limiting chi-square distributions under completely specified (simple) null hypotheses and random censorship. Limiting distributions of the generalized chi-square goodness of fit tests are also established when using minimum chi-square estimation for composite parametric null hypotheses. Tests of fit for negative- exponential and Weibull survival distributions are illustrated for a group of breast cancer patients.
Resource Type	Dissertation
Date Available	2013-06-26T21:42:34+00:00
Date Issued	1974-08-09
Degree Level	Doctoral
Degree Name	Doctor of Philosophy (Ph.D.)
Degree Field	Statistics
Degree Grantor	Oregon State University
Commencement Year	1975
Advisor	Thomas, David R.
Academic Affiliation	Statistics
Non-Academic Affiliation	Oregon State University. Graduate School
Subject	Statistical hypothesis testing
Declaração de direitos	Copyright Not Evaluated
Publisher	Oregon State University
Peer Reviewed	No
Language	English [eng]
Digitization Specifications	File scanned at 300 ppi (Monochrome) using Capture Perfect 3.0.82 on a Canon DR-9080C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces	http://hdl.handle.net/1957/39778

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