plot_evaluation {DySS} | R Documentation |
Evaluate and Visualize Control Charts by ROC curves
Description
Evaluate and Visualize Control Charts by ROC curves
Usage
plot_evaluation(evaluate_control_chart)
Arguments
evaluate_control_chart |
an object of class evaluate_control_chart. |
Value
No return value, called for drawing two ROC plots.
Examples
result_pattern<-estimate_pattern_long_surv(
data_array=data_example_long_surv$data_array_IC,
time_matrix=data_example_long_surv$time_matrix_IC,
nobs=data_example_long_surv$nobs_IC,
starttime=data_example_long_surv$starttime_IC,
survtime=data_example_long_surv$survtime_IC,
survevent=data_example_long_surv$survevent_IC,
design_interval=data_example_long_surv$design_interval,
n_time_units=data_example_long_surv$n_time_units,
estimation_method="risk",
smoothing_method="local linear",
bw_beta=0.05,
bw_mean=0.1,
bw_var=0.1)
result_monitoring<-monitor_long_surv(
data_array_new=data_example_long_surv$data_array_IC,
time_matrix_new=data_example_long_surv$time_matrix_IC,
nobs_new=data_example_long_surv$nobs_IC,
pattern=result_pattern,
method="risk",
parameter=0.5)
output_evaluate<-evaluate_control_chart_one_group(
chart_matrix=result_monitoring$chart,
time_matrix=data_example_long_surv$time_matrix_IC,
nobs=data_example_long_surv$nobs_IC,
starttime=rep(0,nrow(data_example_long_surv$time_matrix_IC)),
endtime=rep(1,nrow(data_example_long_surv$time_matrix_IC)),
status=data_example_long_surv$survevent_IC,
design_interval=data_example_long_surv$design_interval,
n_time_units=data_example_long_surv$n_time_units,
no_signal_action="maxtime")
plot_evaluation(output_evaluate)
plot_PMROC(output_evaluate)
[Package DySS version 1.0 Index]