Description Usage Arguments Details Value Author(s) References See Also Examples
The function arguments are time vector, and censoring indicator vector to compute the maximum liklihood estimator of a parametric model.
1 |
time |
A vector of positive integers, the survival time. |
censor |
The survival indicator, 0 if censored, 1 for event. |
family |
A string indicating the parametric family to fit. Options are |
initial |
A list of initial parameters for optimization, |
This function essentially returns the maximization of likelihood function according to the density function which is indicated by a user in the family
item. The method uses the optim
function with "BFGS" option.
Every element in the time
vector indicates the time that event occurs for one individual, and if the element in the censor
vector is 1 indicates the individual is censored.
shape.fit |
The estimated value for the shape parameter. |
rate.fit |
The estimated value for the rate parameter. |
scale.fit |
If |
meanlog.fit |
If |
sdlog.fit |
If |
shape.sd |
The estimated standard error for |
rate.sd |
The estimated standard error for |
scale.sd |
The estimated standard error for |
meanlog.sd |
The estimated standard error for |
sdlog.sd |
The estimated standard error for |
loglike.maximum |
The value of maximization of the likelihood function. |
hessian |
A symmetric matrix giving an estimation of the minus Hessian at the solution. |
code |
An integer code, 0 indicates successful completion. Other integers indicate possible error codes. See |
iteration |
A two-element integer vector giving the number of calls related to the optimizing function and its gradient. See |
model |
The model for the fitting algorithm, the same as the |
Pierre-Jerome Bergeron and Vahid Partovi Nia.
Jaime Younger. (2011) Goodness-of-Fit for Length-Biased Survival Data with Right-Censoring.
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