The Performance of the Maximum Likelihood Estimator for the Bell Distribution for Count Data

David E. A. Giles

Journal of Modern Applied Statistical Methods2024https://doi.org/10.56801/jmasm.v23.i2.3article
ABDC B
Weight
0.30

Abstract

The single-parameter “Bell distribution” for discrete data allows for over-dispersion in the data. The maximum likelihood estimator for its parameter is downward-biased in finite samples. We consider various methods for reducing this bias. A simulation study shows that these are effective and also lead to a small improvement in the mean squared error of the estimator. The Cox-Snell correction is the recommended. choice among the options that are considered.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.56801/jmasm.v23.i2.3

Or copy a formatted citation

@article{david2024,
  title        = {{The Performance of the Maximum Likelihood Estimator for the Bell Distribution for Count Data}},
  author       = {David E. A. Giles},
  journal      = {Journal of Modern Applied Statistical Methods},
  year         = {2024},
  doi          = {https://doi.org/https://doi.org/10.56801/jmasm.v23.i2.3},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

The Performance of the Maximum Likelihood Estimator for the Bell Distribution for Count Data

Flags are reviewed by the Arbiter methodology team within 5 business days.


Evidence weight

0.30

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.00 × 0.4 = 0.00
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.