View source: R/addendum_search_CL.R
search_CL | R Documentation |
Given a chart matrix, the function search_CL
searches the control limit (CL)
so that the specified average time to signals (ATS) can be attained.
search_CL( chart_matrix, time_matrix, nobs, starttime, endtime, design_interval, n_time_units, time_unit, ATS_nominal, CL_lower, CL_step, CL_upper, no_signal_action = "omit", ATS_tol, CL_tol )
chart_matrix |
charting statistics arranged as a numeric matrix. |
time_matrix |
observation times arranged as a numeric matrix. |
nobs |
number of observations arranged as an integer vector. |
starttime |
a vector of times from the start of monitoring. |
endtime |
a vector of times from the start of monitoring. |
design_interval |
a numeric vector of length two that
gives the left- and right- limits of the design interval.
By default, |
n_time_units |
an integer value that gives the number of basic time units
in the design time interval. |
time_unit |
an optional numeric value of basic time unit. Only used when |
ATS_nominal |
a numeric value. |
CL_lower, CL_step, CL_upper |
three numeric values. |
no_signal_action |
a character specifying the method to use when a signal is not given to a process.
If |
ATS_tol |
a numeric value. |
CL_tol |
a numeric value. |
Search Control Limit
a numeric value, the control limit that gives the desired ATS.
result_pattern<-estimate_pattern_long_1d( data_matrix=data_example_long_1d$data_matrix_IC, time_matrix=data_example_long_1d$time_matrix_IC, nobs=data_example_long_1d$nobs_IC, design_interval=data_example_long_1d$design_interval, n_time_units=data_example_long_1d$n_time_units, estimation_method="meanvar", smoothing_method="local linear", bw_mean=0.1, bw_var=0.1) result_monitoring<-monitor_long_1d( data_matrix_new=data_example_long_1d$data_matrix_IC, time_matrix_new=data_example_long_1d$time_matrix_IC, nobs_new=data_example_long_1d$nobs_IC, pattern=result_pattern, side="upward", chart="CUSUM", method="standard", parameter=0.5) CL<-search_CL( chart_matrix=result_monitoring$chart, time_matrix=data_example_long_1d$time_matrix_IC, nobs=data_example_long_1d$nobs_IC, starttime=rep(0,nrow(data_example_long_1d$time_matrix_IC)), endtime=rep(1,nrow(data_example_long_1d$time_matrix_IC)), design_interval=data_example_long_1d$design_interval, n_time_units=data_example_long_1d$n_time_units, ATS_nominal=200,CL_lower=0,CL_upper=5)
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