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An implementation of the Log Cumulative Probability Model (LCPM) and Proportional Probability Model (PPM) for which the Maximum Likelihood Estimates are determined using constrained optimization. This implementation accounts for the implicit constraints on the parameter space. Other features such as standard errors, z tests and p-values use standard methods adapted from the results based on constrained optimization.
| Version: | 0.1.1 |
| Depends: | plyr (≥ 1.8.4), numDeriv (≥ 2016.8-1), Matrix (≥ 1.2-11), stats (≥ 3.4.2) |
| Published: | 2020-01-09 |
| Author: | Gurbakhshash Singh and Gordon Hilton Fick |
| Maintainer: | Gurbakhshash Singh <gsingh at ccsu.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | lcpm results |
| Reference manual: | lcpm.pdf |
| Package source: | lcpm_0.1.1.tar.gz |
| Windows binaries: | r-devel: lcpm_0.1.1.zip, r-release: lcpm_0.1.1.zip, r-oldrel: lcpm_0.1.1.zip |
| macOS binaries: | r-release (arm64): lcpm_0.1.1.tgz, r-oldrel (arm64): lcpm_0.1.1.tgz, r-release (x86_64): lcpm_0.1.1.tgz, r-oldrel (x86_64): lcpm_0.1.1.tgz |
| Old sources: | lcpm archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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