Science Score: 36.0%
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Repository
Fitting point process models using the Palm likelihood
Basic Info
- Host: GitHub
- Owner: b-steve
- Language: R
- Default Branch: master
- Size: 359 KB
Statistics
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
palm: A package to fit point process models via the Palm likelihood
First proposed by Tanaka, Ogata, and Stoyan (2008), maximisation of the Palm likelihood can provide computationally efficient parameter estimation for point process models in situations where the full likelihood is intractable. This package contains functions to fit a variety of point process models, but is chiefly concerned with Neyman-Scott point processes (NSPPs).
The development of this package was motivated by the analysis of capture-recapture surveys on which individuals cannot be identified---the data from which can conceptually be seen as a NSPP (Fewster, Stevenson, and Borchers, 2016). As such, some of the functions in this package are specifically for the estimation of cetacean density from two-camera aerial surveys; see Stevenson, Borchers, and Fewster (2019).
This package can also fit void processes, which, along with NSPPs, have been fitted to patterns of colon cancer and stroma cell locations (Jones-Todd et al., 2019).
Installation
The stable version of this package can be installed from CRAN:
install.packages("palm")
References
Fewster, R. M., Stevenson, B. C., and Borchers, D. L. (2016) Trace-contrast methods for capture-recapture without capture histories. Statistical Science, 31: 245--258.
Jones-Todd, C. M., Caie, P., Illian, J. B., Stevenson, B. C., Savage, A., Harrison, D. J., and Bown, J. L. (2019). Identifying prognostic structural features in tissue sections of colon cancer patients using point pattern analysis. Statistics in Medicine, 38: 1421--1441.
Stevenson, B. C., Borchers, D. L., and Fewster, R. M. (2019) Cluster capture-recapture to account for identification uncertainty on aerial surveys of animal populations. Biometrics, 75: 326--336.
Tanaka, U., Ogata, Y., and Stoyan, D. (2008) Parameter estimation and model selection for Neyman-Scott point processes. Biometrical Journal, 50: 43--57.
Owner
- Name: Ben Stevenson
- Login: b-steve
- Kind: user
- Location: Auckland, New Zealand
- Company: University of Auckland
- Website: bcstevenson.nfshost.com
- Repositories: 6
- Profile: https://github.com/b-steve
GitHub Events
Total
- Push event: 4
Last Year
- Push event: 4
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Ben Stevenson | b****n@a****z | 239 |
| Ben Stevenson | b****5@s****k | 127 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 1
- Total pull requests: 0
- Average time to close issues: about 8 hours
- Average time to close pull requests: N/A
- Total issue authors: 1
- Total pull request authors: 0
- Average comments per issue: 3.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- pwn1 (1)
Pull Request Authors
Top Labels
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Packages
- Total packages: 1
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Total downloads:
- cran 302 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 8
- Total maintainers: 1
cran.r-project.org: palm
Fitting Point Process Models via the Palm Likelihood
- Homepage: https://github.com/b-steve/palm
- Documentation: http://cran.r-project.org/web/packages/palm/palm.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL]
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Latest release: 1.1.6
published 12 months ago
Rankings
Maintainers (1)
Dependencies
- R >= 3.0.0 depends
- Rcpp >= 0.11.5 depends
- R6 * imports
- gsl * imports
- methods * imports
- minqa * imports
- mvtnorm * imports
- testthat * suggests