Superefficient Estimation of Future Conditional Hazards Based on Marker Information


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Documentation for package ‘HQM’ version 1.0

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auc.hqm AUC for the High Quality Marker estimator
bs.hqm Brier score for the High Quality Marker estimator
b_selection Cross validation bandwidth selection
b_selection_prep_g Preparations for bandwidth selection
Conf_bands Confidence bands
dataset_split Split dataset for K-fold cross validation
dij D matrix entries, used for the implementation of the local linear kernel
Epan Epanechnikov kernel
get_alpha Marker-only hazard rate
get_h_x Local constant future conditional hazard rate estimator
get_h_xll Local linear future conditional hazard rate estimator
g_xt Computation of a key component for wild bootstrap
h_xt Local constant future conditional hazard rate estimation at a single time point
h_xtll Local linear future conditional hazard rate estimation at a single time point
h_xt_vec Hqm estimator on the marker grid
K_b Classical (unmodified) kernel and related functionals
K_b_mat Classical (unmodified) kernel and related functionals
lin_interpolate Linear interpolation
llK_b Local linear kernel
make_N Occurance and Exposure on grids
make_Ni Occurance and Exposure on grids
make_sf Survival function from a hazard
make_Y Occurance and Exposure on grids
make_Yi Occurance and Exposure on grids
pbc2 Mayo Clinic Primary Biliary Cirrhosis Data
pbc2.id Mayo Clinic Primary Biliary Cirrhosis Data
prep_boot Precomputation for wild bootstrap
prep_cv Prepare for Cross validation bandwidth selection
Q1 Bandwidth selection score Q1
R_K Bandwidth selection score R
sn.0 Local linear weight functions
sn.1 Local linear weight functions
sn.2 Local linear weight functions
to_id Event data frame
xK_b Classical (unmodified) kernel and related functionals