Package: defm 0.2.1.0
defm: Estimation and Simulation of Multi-Binary Response Models
Multi-binary response models are a class of models that allow for the estimation of multiple binary outcomes simultaneously. This package provides functions to estimate and simulate these models using the Discrete Exponential-Family Models [DEFM] framework. In it, we implement the models described in Vega Yon, Valente, and Pugh (2023) <doi:10.48550/arXiv.2211.00627>. DEFMs include Exponential-Family Random Graph Models [ERGMs], which characterize graphs using sufficient statistics, which is also the core of DEFMs. Using sufficient statistics, we can describe the data through meaningful motifs, for example, transitions between different states, joint distribution of the outcomes, etc.
Authors:
defm_0.2.1.0.tar.gz
defm_0.2.1.0.tar.gz(r-4.7-arm64)defm_0.2.1.0.tar.gz(r-4.7-x86_64)defm_0.2.1.0.tar.gz(r-4.6-arm64)defm_0.2.1.0.tar.gz(r-4.6-x86_64)
defm_0.2.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
defm/json (API)
NEWS
| # Install 'defm' in R: |
| install.packages('defm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/uofuepibio/defm/issues
Pkgdown/docs site:https://uofuepibio.github.io
- valentesns - Valente's SNS data
- valentesnsList - Valente's SNS data
Last updated from:304d7ea704. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 139 | ||
| linux-devel-x86_64 | OK | 122 | ||
| source / vignettes | OK | 173 | ||
| linux-release-arm64 | OK | 146 | ||
| linux-release-x86_64 | OK | 158 | ||
| wasm-release | OK | 115 |
Exports:defm_mleget_countersget_statsget_X_namesget_Y_namesinit_defmloglike_defmlogoddsmorder_defmmotif_censusncol_defm_xncol_defm_ynew_defmnobs_defmnrow_defmnterms_defmprint_statsrule_constrain_supportrule_not_one_to_zeroset_counter_infoset_counters_namessim_defmsummary_tabletd_formulatd_generictd_logit_intercepttd_onestexreg_fancy
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Discrete Exponential Family Model (DEFM) | DEFM defm init_defm morder_defm ncol_defm_x ncol_defm_y new_defm new_defm_cpp nobs_defm nrow_defm nterms_defm print_stats |
| Model specification for DEFM | +.DEFM defm_terms rule_constrain_support rule_not_one_to_zero td_formula td_generic td_logit_intercept td_ones terms_defm |
| Access to the names of a model's datasets | defm-names get_X_names get_Y_names |
| Extract the counters from a DEFM model | as.list.DEFM_counter as.list.DEFM_counters get_counters length.DEFM_counters set_counters_names set_counters_names.DEFM set_counters_names.DEFM_counters set_counter_info [.DEFM_counters |
| Get sufficient statistics counts | get_stats |
| Log-Likelihood of DEFM | loglike_defm |
| Maximum Likelihood Estimation of DEFM | defm_mle logodds summary_table texreg_fancy |
| Motif census | defm_motif_census motif_census |
| Simulate data using a DEFM | sim_defm |
| Valente's SNS data | valentesns valentesnsList |
