Description Usage Arguments Value Examples
inter_bch
returns a list with the estimated parameters par
and
their asymptotic covariance matrix mcov
. The list also contains a
dummy variable stop_c
assuming 0 if algorithm converged and 1 if a
stop criteria ended the process.
1 2 |
dataset |
Dataset used to fit the model. |
left |
Vector containing the last check times before event. |
right |
Vector containing the first check times after event. |
cov |
String vector containing the column names to be used on the cure rate predictor. |
sigma |
Parameter for the primal-dual interior-point algorithm used on the maximization process. Default value set to 10. |
crit_theta |
The effects minimum error for convergence purposes. |
crit_p |
Minimum error of the non-parametric cumulative distribution function. |
max_n |
Maximum number of iterations of the ECM algorithm. |
output_files |
Boolean indicating if text outputs for the estimates and variances should be generated. |
The inter_bch
function returns an list containing the
following outputs:
|
estimates of theta parameters. |
|
estimates for the asymptotic covariance matrix of theta parameters. |
|
stop criteria indicator assuming 1 when process is stopped for a non-convergence criteria. Assumes 0 when convergence is reached. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | set.seed(3)
sample_set <- sim_bch(80)
## few iterations just to check how to use the function
inter_bch(sample_set, sample_set$L,
sample_set$R, c("xi1","xi2"), max_n = 5)
## precise estimate (computationally intensive)
## Not run:
inter_bch(sample_set, sample_set$L, sample_set$R, c("xi1","xi2"))
## End(Not run)
|
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