On a loss-based prior for the number of components in mixture models
Publication
, Journal Article
Grazian, C; Villa, C; Liseo, B
Published in: Statistics and Probability Letters
March 1, 2020
We introduce a prior distribution for the number of components of a mixture model. The prior considers the worth of each possible mixture, measured by a loss function with two components: one measures the loss in information in choosing the wrong mixture and one the loss due to complexity.
Duke Scholars
Published In
Statistics and Probability Letters
DOI
ISSN
0167-7152
Publication Date
March 1, 2020
Volume
158
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics
- 0102 Applied Mathematics
Citation
APA
Chicago
ICMJE
MLA
NLM
Grazian, C., Villa, C., & Liseo, B. (2020). On a loss-based prior for the number of components in mixture models. Statistics and Probability Letters, 158. https://doi.org/10.1016/j.spl.2019.108656
Grazian, C., C. Villa, and B. Liseo. “On a loss-based prior for the number of components in mixture models.” Statistics and Probability Letters 158 (March 1, 2020). https://doi.org/10.1016/j.spl.2019.108656.
Grazian C, Villa C, Liseo B. On a loss-based prior for the number of components in mixture models. Statistics and Probability Letters. 2020 Mar 1;158.
Grazian, C., et al. “On a loss-based prior for the number of components in mixture models.” Statistics and Probability Letters, vol. 158, Mar. 2020. Scopus, doi:10.1016/j.spl.2019.108656.
Grazian C, Villa C, Liseo B. On a loss-based prior for the number of components in mixture models. Statistics and Probability Letters. 2020 Mar 1;158.
Published In
Statistics and Probability Letters
DOI
ISSN
0167-7152
Publication Date
March 1, 2020
Volume
158
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics
- 0102 Applied Mathematics