hdslc.fast: Hazard discrimination summary estimate (local constant) at...
In liangcj/hds: Hazard Discrimination Summary
Description
Usage
Arguments
Details
Value
Description
hdslc.fast estimates HDS at a single time using the local-in-time
proportional hazards model. See Cai and Sun (2003, Scandinavian Journal of
Statistics) for details on the local-in-time PH model.
Usage
1
hdslc.fast(S, betahat, m)
Arguments
S
A vector of length nrow(m) (which is typically the number of
observations n), where each value is the subject-specific survival at time t
where t is implied by the choice of betahat.
betahat
A p x 1 vector of coefficient estimates at time t of interest
from the local-in-time Cox model. Vector length p is the number of
covariates. Typically the output from hdslc::finda is passed here.
m
A numeric n x p matrix of covariate values, with a column for each
covariate and each observation is on a separate row.
Details
The user typically will not interact with this function. Rather, hdslc
wraps this function and is what the user typically will use.
Value
The HDS estimate at times t, where t is implied by choice of S
and betahat passed to hdslc.fast.
liangcj/hds documentation built on May 21, 2019, 6:11 a.m.
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Description Usage Arguments Details Value
Description
hdslc.fast estimates HDS at a single time using the local-in-time
proportional hazards model. See Cai and Sun (2003, Scandinavian Journal of
Statistics) for details on the local-in-time PH model.
Usage
1 | hdslc.fast(S, betahat, m)
|
Arguments
S |
A vector of length |
betahat |
A p x 1 vector of coefficient estimates at time t of interest
from the local-in-time Cox model. Vector length p is the number of
covariates. Typically the output from |
m |
A numeric n x p matrix of covariate values, with a column for each covariate and each observation is on a separate row. |
Details
The user typically will not interact with this function. Rather, hdslc
wraps this function and is what the user typically will use.
Value
The HDS estimate at times t, where t is implied by choice of S
and betahat passed to hdslc.fast.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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