Description Usage Format Value Fields Methods See Also

Class for NHPP-based software reliability model with d-metrics

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`R6Class`

object.

Object of `R6Class`

with methods for NHPP-based software reliability model with d-metrics.

`name`

A character string for the name of model.

`params`

A numeric vector for the model parameters.

`df`

An integer for the degrees of freedom of the model.

`data`

Data to esimate parameters.

`print()`

This method prints model parameters.

`omega()`

This method returns the number of total faults.

`coefficients()`

This method returns a vector for the coefficients.

`mvf(t, data = NULL)`

This method returns the mean value function at time t. The d-metrics is given from

`data`

. If`data`

is NULL, the d-metrics for the estimation is used.`dmvf(t, data = NULL)`

This method returns the intensity function at time t. The d-metrics is given from

`data`

. If`data`

is NULL, the d-metrics for the estimation is used.`residual(t, data = NULL)`

This method returns the expected residual number of faults at time t. The d-metrics is given from

`data`

. If`data`

is NULL, the d-metrics for the estimation is used.`ffp(t, data = NULL)`

This method returns the fault-free probability at time t. The d-metrics is given from

`data`

. If`data`

is NULL, the d-metrics for the estimation is used.`init_params(data)`

This method changes the model parameters based on a given data. This is used to set the initial value for the fitting algorithm.

`set_params(params)`

This method sets the model parameters.

`set_data(data)`

This method sets data.

`em(params, data)`

This method returns a list with an updated parameter vector (param), absolute difference of parameter vector (pdiff), log-likelihood function for a given parameter vector (llf), the number of total faults (total) via EM algorithm for a given data.

`llf(data)`

This method returns the log-likelihood function for a given data.

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