CovMatComp: Output the entire martingale and counting process covariance...
In blangworthy/survPCA: Estimation of PCA for Survival Data
Description
Usage
Arguments
Value
Description
This takes survival times and censoring/cause indicators for p different variables and outputs the p times p martingale and counting process covariance/correlation matrices for all variables in the presence of competing risks.
Usage
1
CovMatComp(data, causes, p = NA, t, mineigen = 0.001)
Arguments
data
A matrix where the first p columns are the event times for the p variables and the next p columns are the censoring/cause indicators for the p variables. The order for the event times and censoring/cause indicators needs to be the same.
causes
A p-dimensional vector that has the causes for each of the p different variables.
p
The number of variables to calculate the matrix for, if NA ncol(data)/2 will be used
t
The timepoint to estimate the covariance and correlation matrices
mineigen
The minimum eigenvalue for the martingale and counting process covariance matrices if not already positive semidefinite
Value
A list with the following elements
CovMartComp: The full martingale covariance matrix
CorMartComp: The full martingale correlation matrix
CovCountComp: The full counting process covariance matrix
CorCountComp: The full counting process correlation matrix
blangworthy/survPCA documentation built on Oct. 3, 2020, 3:04 p.m.
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.
Description Usage Arguments Value
Description
This takes survival times and censoring/cause indicators for p different variables and outputs the p times p martingale and counting process covariance/correlation matrices for all variables in the presence of competing risks.
Usage
1 | CovMatComp(data, causes, p = NA, t, mineigen = 0.001)
|
Arguments
data |
A matrix where the first p columns are the event times for the p variables and the next p columns are the censoring/cause indicators for the p variables. The order for the event times and censoring/cause indicators needs to be the same. |
causes |
A p-dimensional vector that has the causes for each of the p different variables. |
p |
The number of variables to calculate the matrix for, if NA ncol(data)/2 will be used |
t |
The timepoint to estimate the covariance and correlation matrices |
mineigen |
The minimum eigenvalue for the martingale and counting process covariance matrices if not already positive semidefinite |
Value
A list with the following elements
CovMartComp: The full martingale covariance matrix
CorMartComp: The full martingale correlation matrix
CovCountComp: The full counting process covariance matrix
CorCountComp: The full counting process correlation matrix
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.