Goodness-of-fit test for discrete and censored data, based on the empirical distribution function
In this thesis two general problems concerning goodness-of- fit statistics based on the empirical distribution are considered. The first concerns the problem of adapting Kolmogorov-Smirnov type statistics to test for discrete populations. The significance points of the statistics are given and vario...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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1973
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| Online Access: | https://eprints.nottingham.ac.uk/11257/ |
| _version_ | 1848791232175669248 |
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| author | Pettitt, Anthony |
| author_facet | Pettitt, Anthony |
| author_sort | Pettitt, Anthony |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | In this thesis two general problems concerning goodness-of- fit statistics based on the empirical distribution are considered. The first concerns the problem of adapting Kolmogorov-Smirnov type statistics to test for discrete populations. The significance points of the statistics are given and various power comparisons made.
The second problem concerns testing for goodness-of-fit with censored data using the Cramér-von Mises type statistics. The small and large sample distributions are given and the tests are modified so that they can be used to test for the normal and the exponential distributions. The asymptotic theory is developed. Percentage points for the statistics are given and various small sample and large sample power studies are made, for the various cases. |
| first_indexed | 2025-11-14T18:25:14Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-11257 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:25:14Z |
| publishDate | 1973 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-112572025-02-28T11:12:18Z https://eprints.nottingham.ac.uk/11257/ Goodness-of-fit test for discrete and censored data, based on the empirical distribution function Pettitt, Anthony In this thesis two general problems concerning goodness-of- fit statistics based on the empirical distribution are considered. The first concerns the problem of adapting Kolmogorov-Smirnov type statistics to test for discrete populations. The significance points of the statistics are given and various power comparisons made. The second problem concerns testing for goodness-of-fit with censored data using the Cramér-von Mises type statistics. The small and large sample distributions are given and the tests are modified so that they can be used to test for the normal and the exponential distributions. The asymptotic theory is developed. Percentage points for the statistics are given and various small sample and large sample power studies are made, for the various cases. 1973 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/11257/1/468818.pdf Pettitt, Anthony (1973) Goodness-of-fit test for discrete and censored data, based on the empirical distribution function. PhD thesis, University of Nottingham. goodness-of-fit statistics empirical distribution |
| spellingShingle | goodness-of-fit statistics empirical distribution Pettitt, Anthony Goodness-of-fit test for discrete and censored data, based on the empirical distribution function |
| title | Goodness-of-fit test for discrete and censored data, based on the empirical distribution function |
| title_full | Goodness-of-fit test for discrete and censored data, based on the empirical distribution function |
| title_fullStr | Goodness-of-fit test for discrete and censored data, based on the empirical distribution function |
| title_full_unstemmed | Goodness-of-fit test for discrete and censored data, based on the empirical distribution function |
| title_short | Goodness-of-fit test for discrete and censored data, based on the empirical distribution function |
| title_sort | goodness-of-fit test for discrete and censored data, based on the empirical distribution function |
| topic | goodness-of-fit statistics empirical distribution |
| url | https://eprints.nottingham.ac.uk/11257/ |