fitit {icpack} | R Documentation |
Fit proportional hazard model with smooth baseline hazard and (optional) interval censoring
fitit(
Y,
R,
dead,
X,
B,
Ic,
R1,
cbx,
Pdiff,
Pridge,
lambda,
nit = 50,
tol = 1e-06,
tollam = 0.01,
update_lambda = FALSE,
ic_update = TRUE,
monitor = FALSE
)
Y |
Events (matrix, number of bins by subjects) |
R |
Risk sets (matrix, number of bins by subjects) |
dead |
(Boolean vector, TRUE if event, FALSE if right censored) |
X |
Covariates (matrix, number of covariates (+1) by subjects) |
B |
B-spline basis matrix |
Ic |
Censoring interval per individual, coded as 0/1 (in columns) |
R1 |
Left truncation interval per individual, coded as 0/1 (in columns) |
cbx |
Vector of starting values |
Pdiff |
B-spline part of penalty matrix |
Pridge |
Ridge part of penalty matrix (for intercept) |
lambda |
Smoothing parameter (number) |
nit |
Maximum number of iterations (integer) |
tol |
Tolerance for final fit |
tollam |
Tolerance for switching to lambda update |
update_lambda |
Automatic update of lambda (Boolean) |
ic_update |
Update risk and event probabilities (Boolean) |
monitor |
Monitor convergence (Boolean) |
A list with items
cbx |
Vector of |
ll |
Poisson GLM log-likelihood |
lambda |
Final tuning parameter |
pen |
Penalty part of penalized log-likelihood |
ed |
Effetive dimension of the baseline hazard |
nit1 |
Number of iterations used in first phase |
nit |
Total number of iterations used (first plus second phase) |
tollam |
Tolerance used for switching to lambda update |