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HQM (version 0.1.1)

Superefficient Estimation of Future Conditional Hazards Based on Marker Information

Description

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.

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Version

Install

install.packages('HQM')

Monthly Downloads

250

Version

0.1.1

License

GPL (>= 2)

Maintainer

Dimitrios Bagkavos

Last Published

September 24th, 2024

Functions in HQM (0.1.1)

get_alpha

Marker-only hazard rate

llK_b

Local linear kernel

llweights

Local linear weight functions

prep_boot

Precomputation for wild bootstrap

make_sf

Survival function from a hazard

prep_cv

Prepare for Cross validation bandwidth selection

to_id

Event data frame

pbc2

Mayo Clinic Primary Biliary Cirrhosis Data

b_selection

Cross validation bandwidth selection

b_selection_prep_g

Preparations for bandwidth selection

dij

D matrix entries, used for the implementation of the local linear kernel

Kernels

Classical (unmodified) kernel and related functionals

make_N, make_Ni, make_Y, make_Yi

Occurance and Exposure on grids

dataset_split

Split dataset for K-fold cross validation

Bandwidth selection score Q1

R_K

Bandwidth selection score R

get_h_x

Local constant 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

lin_interpolate

Linear interpolation

h_xt_vec

Hqm estimator on the marker grid

get_h_xll

Local linear future conditional hazard rate estimator