Small-sample estimation of negative binomial dispersion, with applications to SAGE data

Clicks: 47
ID: 297423
2007
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Abstract
We derive a quantile-adjusted conditional maximum likelihood estimator for the dispersion parameter of the negative binomial distribution and compare its performance, in terms of bias, to various other methods. Our estimation scheme outperforms all other methods in very small samples, typical of those from serial analysis of gene expression studies, the motivating data for this study. The impact of dispersion estimation on hypothesis testing is studied. We derive an "exact" test that outperforms the standard approximate asymptotic tests.
Reference Key
openalex_W2141425631 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Mark D. Robinson, Gordon K. Smyth
Journal epidemiology biostatistics and public health
Year 2007
DOI
10.1093/biostatistics/kxm030
URL
https://academic.oup.com/biostatistics/article-pdf/9/2/321/17734659/kxm030.pdf
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