Package: EMLI 0.2.0
EMLI: Computationally Efficient Maximum Likelihood Identification of Linear Dynamical Systems
Provides implementations of computationally efficient maximum likelihood parameter estimation algorithms for models that represent linear dynamical systems. Currently, one such algorithm is implemented for the one-dimensional cumulative structural equation model with shock-error output measurement equation and assumptions of normality and independence. The corresponding scientific paper is yet to be published, therefore the relevant reference will be provided later.
Authors:
EMLI_0.2.0.tar.gz
EMLI_0.2.0.zip(r-4.5)EMLI_0.2.0.zip(r-4.4)EMLI_0.2.0.zip(r-4.3)
EMLI_0.2.0.tgz(r-4.4-any)EMLI_0.2.0.tgz(r-4.3-any)
EMLI_0.2.0.tar.gz(r-4.5-noble)EMLI_0.2.0.tar.gz(r-4.4-noble)
EMLI_0.2.0.tgz(r-4.4-emscripten)EMLI_0.2.0.tgz(r-4.3-emscripten)
EMLI.pdf |EMLI.html✨
EMLI/json (API)
NEWS
| # Install 'EMLI' in R: |
| install.packages('EMLI', repos = c('https://vy-du.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 2 years agofrom:14f70fed52. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 16 2024 |
| R-4.5-win | OK | Nov 16 2024 |
| R-4.5-linux | OK | Nov 16 2024 |
| R-4.4-win | OK | Nov 16 2024 |
| R-4.4-mac | OK | Nov 16 2024 |
| R-4.3-win | OK | Nov 16 2024 |
| R-4.3-mac | OK | Nov 16 2024 |
Exports:calculate_likelihoodestimate_parametersevaluate_estimatesgenerate_data
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| calculate_likelihood | calculate_likelihood |
| estimate_parameters | estimate_parameters |
| evaluate_estimates | evaluate_estimates |
| generate_data | generate_data |
