Package: cta 1.3.0
Qiansheng Zhu
cta: Contingency Table Analysis Based on ML Fitting of MPH Models
Contingency table analysis is performed based on maximum likelihood (ML) fitting of multinomial-Poisson homogeneous (MPH) and homogeneous linear predictor (HLP) models. See Lang (2004) <doi:10.1214/aos/1079120140> and Lang (2005) <doi:10.1198/016214504000001042> for MPH and HLP models. Objects computed include model goodness-of-fit statistics; likelihood- based (cell- and link-specific) residuals; and cell probability and expected count estimates along with standard errors. This package can also compute test-inversion--e.g. Wald, profile likelihood, score, power-divergence--confidence intervals for contingency table estimands, when table probabilities are potentially subject to equality constraints. For test-inversion intervals, see Lang (2008) <doi:10.1002/sim.3391> and Zhu (2020) <doi:10.17077/etd.005331>.
Authors:
cta_1.3.0.tar.gz
cta_1.3.0.tar.gz(r-4.5-noble)cta_1.3.0.tar.gz(r-4.4-noble)
cta_1.3.0.tgz(r-4.4-emscripten)cta_1.3.0.tgz(r-4.3-emscripten)
cta.pdf |cta.html✨
cta/json (API)
# Install 'cta' in R: |
install.packages('cta', 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 3 years agofrom:7970b1ced0. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 23 2024 |
R-4.5-linux | OK | Dec 23 2024 |
Exports:block.fctcheck.HLPcheck.homogcheck.zero.order.homogci.tablecompute_cons_MLE_asecreate.Ucreate.Z.ZFdiff_Gsq_nrdiff_Gsq_robustdiff_PD_nrdiff_PD_robustdiff_Xsq_nrdiff_Xsq_robustf.psiM.fctmph.fitmph.summarynested_Gsq_nrnested_Gsq_robustnested_PD_nrnested_PD_robustnested_Xsq_nrnested_Xsq_robustnum.deriv.fctquadratic.fitsolve_quadraticWald_trans.Wald_nrWald_trans.Wald_robust