Package: HQM 0.1.1

Dimitrios Bagkavos

HQM: Superefficient Estimation of Future Conditional Hazards Based on Marker Information

Provides a nonparametric smoothed kernel density estimator for the future conditional hazard when time-dependent covariates are present. It also provides pointwise and uniform confidence bands and a bandwidth selection.

Authors:Dimitrios Bagkavos [aut, cre], Alex Isakson [ctb], Enno Mammen [ctb], Jens Nielsen [ctb], Cecile Proust-Lima [ctb]

HQM_0.1.1.tar.gz
HQM_0.1.1.tar.gz(r-4.5-noble)HQM_0.1.1.tar.gz(r-4.4-noble)
HQM_0.1.1.tgz(r-4.4-emscripten)HQM_0.1.1.tgz(r-4.3-emscripten)
HQM.pdf |HQM.html✨
HQM/json (API)

# Install 'HQM' in R:
install.packages('HQM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • pbc2 - Mayo Clinic Primary Biliary Cirrhosis Data

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 333 downloads 31 exports 3 dependencies

Last updated 2 months agofrom:b604ccd47f. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-linuxOKOct 25 2024

Exports:b_selectionb_selection_prep_gConf_bandsdataset_splitdijEpang_xtget_alphaget_h_xget_h_xllh_xth_xt_vech_xtllK_bK_b_matlin_interpolatellK_bmake_Nmake_Nimake_sfmake_Ymake_Yiprep_bootprep_cvQ1R_Ksn.0sn.1sn.2to_idxK_b

Dependencies:latticeMatrixsurvival