An accurate test for the equality of covariance matrices from decomposable graphical Gaussian models
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Bibliographic record
Abstract
Abstract This paper derives a saddlepoint based approximation for the cumulative distribution function of the Bartlett–Box M‐statistic that tests the equality of covariance matrices for several samples from graphical Gaussian models Markov with respect to a decomposable graph . The proposed saddlepoint‐based method has third‐order accuracy ( ). Simulation results show that the proposed method has extremely good coverage properties even when the sample size is small. We apply our method to the well‐known Call Centre data set and show that the covariance matrix is not constant through time. The Canadian Journal of Statistics 42: 61–77; 2014 © 2014 Statistical Society of Canada
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Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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