On approximation of the distribution for Pearson statistic
The paper considers the classical Goodness of Fit test. It suggests to use the Gamma distribution for the approximation of the distribution of the Pearson statistics with unknown parameters estimated from raw data. The parameters of these Gamma distribution can be estimated from the first two...
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| Format: | Journal Article |
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| Online Access: | http://hdl.handle.net/20.500.11937/75739 |
| _version_ | 1848763539436601344 |
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| author | Dokuchaev, Nikolai |
| author_facet | Dokuchaev, Nikolai |
| author_sort | Dokuchaev, Nikolai |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The paper considers the classical Goodness of Fit test.
It suggests to use the Gamma distribution for the approximation of the
distribution of the Pearson statistics with unknown parameters estimated from
raw data. The parameters of these Gamma distribution can be estimated from the
first two moments of the statistic after averaging over a distribution of the
unknown parameter over its range. This allows to simplify calculation of the
quantiles for the Pearson statistic, as is shown in some simulation experiments
with medium and small sample sizes. |
| first_indexed | 2025-11-14T11:05:04Z |
| format | Journal Article |
| id | curtin-20.500.11937-75739 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:05:04Z |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-757392019-06-17T03:37:02Z On approximation of the distribution for Pearson statistic Dokuchaev, Nikolai math.ST math.ST stat.TH 62F03, 62G05, 62G10 The paper considers the classical Goodness of Fit test. It suggests to use the Gamma distribution for the approximation of the distribution of the Pearson statistics with unknown parameters estimated from raw data. The parameters of these Gamma distribution can be estimated from the first two moments of the statistic after averaging over a distribution of the unknown parameter over its range. This allows to simplify calculation of the quantiles for the Pearson statistic, as is shown in some simulation experiments with medium and small sample sizes. Journal Article http://hdl.handle.net/20.500.11937/75739 restricted |
| spellingShingle | math.ST math.ST stat.TH 62F03, 62G05, 62G10 Dokuchaev, Nikolai On approximation of the distribution for Pearson statistic |
| title | On approximation of the distribution for Pearson statistic |
| title_full | On approximation of the distribution for Pearson statistic |
| title_fullStr | On approximation of the distribution for Pearson statistic |
| title_full_unstemmed | On approximation of the distribution for Pearson statistic |
| title_short | On approximation of the distribution for Pearson statistic |
| title_sort | on approximation of the distribution for pearson statistic |
| topic | math.ST math.ST stat.TH 62F03, 62G05, 62G10 |
| url | http://hdl.handle.net/20.500.11937/75739 |