GLAM_1d_covariates {TwoTimeScales} | R Documentation |
Fit the 1d GLAM with covariates
Description
GLAM_1d_covariates()
fits a GLAM for the hazard with one time
scale, with covariates.
Usage
GLAM_1d_covariates(
R,
Y,
Bs,
Z = Z,
Wprior = NULL,
P,
control_algorithm = list(maxiter = 20, conv_crit = 1e-05, verbose = FALSE)
)
Arguments
R |
A 2d-array of dimensions ns by n containing exposure times. |
Y |
A 2d-array of dimensions ns by n containing event indicators. |
Bs |
A matrix of B-splines for the |
Z |
A regression matrix of covariates values of dimensions n by p. |
Wprior |
An optional vector of length ns of a-priori weights. |
P |
The penalty matrix of dimension cs by cs. |
control_algorithm |
A list with optional values for the parameters of
iterative processes:
* |
Value
A list with the following elements:
-
alpha
The vector of estimated P-splines coefficients of length cs. -
SE_alpha
The vector of estimated Standard Errors for thealpha
coefficients, of length cs. -
beta
The vector of length p of estimated covariates coefficients. -
se_beta
The vector of length p of estimated Standard Errors for thebeta
coefficients. -
eta0
The vector of values of the baseline linear predictor (log-hazard). -
H
The hat-matrix. -
Cov
The full variance-covariance matrix. -
deviance
The deviance. -
ed
The effective dimension of the model. -
aic
The value of the AIC. -
bic
The value of the BIC. -
Bbases
a list with the B-spline basisBs
(this is a list for compatibility with functions in 2d).