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Added dichotomize_range(): converts continuous
measurements to a binary indicator based on whether each value falls
inside or outside an acceptable operating range, for practical real-data
use as described in dissertation Section 6.4.1. The range can be
supplied directly as known
lower_limit/upper_limit values, or estimated
from historical reference data using percentiles (default
1st/99th).
Added dichotomize_range_multi(): applies
dichotomize_range() separately to each variable in a
dataset, since different variables monitored together typically have
different acceptable ranges (for example, different variables in the
same process rarely share one tolerance band). Every variable’s range
must be specified explicitly; there is no shared default across
variables.
Added check_stream_correlation(): reports the
pairwise Pearson correlation among candidate streams and flags any pair
whose absolute correlation exceeds a threshold (default 0.3, per
dissertation Section 6.2.7), as a diagnostic check of the independence
assumption underlying the CSB-EWMA chart. This function is diagnostic
only; it does not remove or adjust correlated streams, since no
validated correction method for correlated streams currently exists for
this chart.
Added a stop_at_signal argument to
run_csb_ewma() and csb_ewma(). The default
(stop_at_signal = TRUE) is unchanged from every released
version through 1.1.0: monitoring stops at the first signal. Setting
stop_at_signal = FALSE instead continues monitoring through
max_time, recording every signal in
signal_times without resetting the cumulative sum or EWMA
statistic after a signal. csb_ewma() performs post-hoc
identification separately at each signal in this mode, stored as a named
list in flagged_by_signal (flagged is kept as
the first signal’s result for backward compatibility).
plot.csb_ewma() and plot_csb_ewma_direct()
annotate every signal in signal_times when present. This
continuation mode is a practical convenience for real-time or
dashboard-style monitoring; it is not itself a procedure described in
the dissertation, which presents only the stop-at-first-signal
convention.
Added a verbose argument to csb_ewma()
(default FALSE). When TRUE, prints
informational messages about whether the input data required
dichotomization; these are silent by default.
Fixed a label placement bug in plot.csb_ewma() and
plot_csb_ewma_direct(): the “Signal at t = …” annotation
used hjust = 0 instead of hjust = 1, which
misaligned the label against the signal line.
Fixed a variance-calculation bug in
var_rt_exact_single(): the loop
for (j in 1:(t-1)) evaluated to 1:0 when
t = 1, which R treats as the two-element sequence
c(1, 0) rather than an empty range, so two spurious terms
were added to Var(r_1), inflating it to about 4.8 times its
correct value and widening UCL_1/LCL_1
accordingly. Replaced with seq_len(t - 1), which is empty
when t = 1 as required; Var(r_1) now correctly
equals lambda^2. All other time points are
unaffected.
Fixed a documentation bug: a stray line in the roxygen
@examples blocks for csb_ewma() and
rlaplace() was being included in the generated Rd files’
\examples{} sections, causing R CMD check’s example-parsing
step to fail with a syntax error. Removed.
URL and BugReports fields to
DESCRIPTION, pointing to the package’s development
repository.@seealso cross-references between
run_csb_ewma() and csb_ewma() clarifying that
they are not duplicates: run_csb_ewma() is the lower-level
monitoring engine, useful directly when a variance cache should be
precomputed once and reused across many chart runs (for example, in
simulation studies); csb_ewma() is the higher-level
convenience wrapper that dichotomizes continuous data, precomputes
variance, calls run_csb_ewma(), and performs post-hoc
identification automatically.testthat) covering every exported
function.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.