Package: IsingSampler 0.2.3
Sacha Epskamp
IsingSampler: Sampling Methods and Distribution Functions for the Ising Model
Sample states from the Ising model and compute the probability of states. Sampling can be done for any number of nodes, but due to the intractibility of the Ising model the distribution can only be computed up to ~10 nodes.
Authors:
IsingSampler_0.2.3.tar.gz
IsingSampler_0.2.3.tar.gz(r-4.5-noble)IsingSampler_0.2.3.tar.gz(r-4.4-noble)
IsingSampler_0.2.3.tgz(r-4.4-emscripten)IsingSampler_0.2.3.tgz(r-4.3-emscripten)
IsingSampler.pdf |IsingSampler.html✨
IsingSampler/json (API)
NEWS
| # Install 'IsingSampler' in R: |
| install.packages('IsingSampler', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:d7e39cd8c5. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 17 2024 |
| R-4.5-linux-x86_64 | NOTE | Aug 17 2024 |
Exports:EstimateIsingEstimateIsingBiEstimateIsingLLEstimateIsingPLEstimateIsingUniIsingEntrophyIsingLikelihoodIsingPLIsingSamplerIsingStateProbIsingSumLikelihoodLinTransform
Dependencies:clidplyrfansigenericsgluelifecyclemagrittrnnetpillarpkgconfigplyrR6Rcpprlangtibbletidyselectutf8vctrswithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Sampling methods and distribution functions for the Ising model | IsingSampler-package |
| non-regularized estimation methods for the Ising Model | EstimateIsing EstimateIsingBi EstimateIsingLL EstimateIsingPL EstimateIsingUni |
| Entropy of the Ising Model | IsingEntrophy |
| Likelihood of all states from tractible Ising model. | IsingLikelihood |
| Pseudo-likelihood | IsingPL |
| Sample states from the Ising model | IsingSampler |
| Likelihood of single state from tractible Ising model. | IsingStateProb |
| Likelihood of sumscores from tractible Ising model. | IsingSumLikelihood |
| Transform parameters for linear transformations on response catagories | LinTransform |