The multivariate side of the package now has the natural pair of
memory-based charts. Both follow the calibrate() /
monitor() Phase I / Phase II workflow.
shewhart_mewma() — Multivariate Exponentially Weighted
Moving Average (Lowry, Woodall, Champ & Rigdon 1992). The
multivariate analogue of shewhart_ewma(): joint monitoring
of p > 1 correlated variables for small
persistent shifts in the vector mean. Time-varying and steady-state
covariance both supported. Decision interval h calibrated
by lookup in Prabhu & Runger
ARL_0 ~ 200).shewhart_mcusum() — Multivariate CUSUM (Crosier 1988).
The multivariate analogue of shewhart_cusum(). Uses
Crosier’s shrinkage operator: at each step the cumulative vector is
shrunk towards zero by k / C_i where C_i is
its Mahalanobis norm; if the norm falls below k, the
cumulative vector resets to zero. Decision interval h
calibrated by lookup in Crosier (1988) Table 1 for k = 0.5,
ARL_0 ~ 200, p = 2..10. Phase II monitoring
continues from the calibration’s final S vector (Crosier
1988 §5).autoplot() method now uses
shewhart_palette() and shewhart_theme(), so
plots from any chart family share the same editorial look (off-white
surface, single horizontal grid, bold left-aligned title, sequential
phase palette, hollow firebrick rings on out-of-control points).
Out-of-control marks centralised in a new internal
violation_layers() helper, sized at halo 1.7 / ring 1.4 /
stroke 0.7.Phase 0, Phase 1,
… labels via the phase_n and new legend_phases
locale entries.arl-simulation vignette’s hand-rolled chart was
using theme_minimal() with default ggplot2 colours; now
uses shewhart_theme() and the package palette so it matches
the rest.R/autoplot.R (two
comments, one string literal) replaced with ASCII alternatives or the
— escape so R CMD check no longer warns about
non-ASCII source.This release closes the remaining items from
dev/ROADMAP.md §11 that were left for after v1.1: a plotly
bridge and external numerical validation against the long-established
qcc package.
as_plotly()as_plotly() with a
shewhart_chart method that converts any chart into an
interactive plotly figure. For two-panel charts (I-MR, X̄-R, X̄-S) the
helper produces a plotly::subplot() with a synchronised
x-axis. plotly is in Suggests, so it is only
loaded on demand.tooltip argument is forwarded to
plotly::ggplotly() for full control of what hover boxes
display.tests/testthat/test-vs-qcc.R (skipped silently if
qcc is not installed) compares the limits computed by
shewhartr to the reference values from the qcc
package on its canonical example datasets — pistonrings for
the variables charts, orangejuice for p / np,
circuit for c. Every centre line and 3-sigma limit agrees
with qcc to within 1e-3 absolute tolerance.test-monitor.R no longer triggers the (correct) “small
c_bar” cli_warn from chart-c.R: the test data uses
lambda = 12 so the normal approximation is well-behaved.
The 1-warning warning in devtools::test() is gone; the
suite is now FAIL 0 / WARN 0.This release closes most of the items left open in
dev/ROADMAP.md §11.
shewhart_hotelling() is the package’s first
multivariate chart — a Hotelling T² chart for jointly
monitoring p > 1 correlated variables. Both individual
observations (subgroup = NULL) and subgrouped data are
supported, with the appropriate exact Phase I limits (Beta for
individuals, F for subgroups) and the slightly wider Phase II limits as
derived in Tracy, Young & Mason (1992) and Montgomery (2019, Chapter
11). The implementation follows Mason & Young (2002).T² statistic per row,
its decomposition by variable (the contribution of each variable to the
alarm — useful when T² signals but no univariate chart
does), and a logical flag against the appropriate chart-level UCL.multivariate-charts walks through the standard
worked example: a chemical process with three correlated quality
characteristics, showing how the multivariate chart catches a
correlation-breaking shift that any of the three univariate charts would
miss.monitor() now dispatches to monitor_ewma()
and monitor_cusum() (R/calibrate.R), so the
calibrate(..., chart = "ewma") /
monitor(new_data, calib) workflow now works uniformly
across every chart in the package — not just the Shewhart-style
ones.calibrate() accepts the new keys "ewma",
"cusum", "hotelling".SSgompertzDummy self-starter is more robust: starting
values for b2 and b3 are now derived from the
cumulative-mid-point heuristic rather than hard-coded constants, fixing
the convergence failure with typical sample sizes that previously
required \dontrun{} in the example.This release is a comprehensive reposition of the package. The
original (v0.1.x, distributed as Shewhart) was
COVID-focused and provided a single function family for regression-based
control charts. v1.0.0 is a full general-purpose SPC
toolkit while preserving the regression-chart speciality that motivated
the package.
Rename. As part of the reposition, the package has
been renamed Shewhart → shewhartr to follow
modern lowercase R-package conventions and to free the name “Shewhart”
for the methodology in text and documentation. Update existing code with
library(shewhartr) (formerly
library(Shewhart)).
The API has been substantially redesigned. Existing scripts written
against v0.1.x will not run unchanged.
covid-recife),
not as the organising principle.qcc and
qicharts2, and emphasises five differentiators:
tidyverse-native API, broom integration, regression-based charts as a
first-class citizen, embedded methodology (ARL, Box-Cox, runs tests),
and an explicit Phase I / Phase II workflow.shewhart_i_mr(),
shewhart_xbar_r(), shewhart_xbar_s().shewhart_p(), shewhart_np(),
shewhart_c(), shewhart_u(). The c and u charts
accept limits = "poisson" for exact Poisson quantile limits
rather than the normal approximation.shewhart_regression() replaces the old
shewhart() function with a cleaner API, an extensible model
menu (auto, linear, log,
loglog, gompertz, logistic, plus
user formulas), automatic phase detection via configurable runs rules,
and proper handling of irregular time grids.shewhart_ewma() (Roberts 1959) for
the Exponentially Weighted Moving Average chart, with both time-varying
and steady-state limits, and shewhart_cusum() (Page 1954)
for the two-sided tabular CUSUM chart with configurable reference value
k and decision interval h. Both fit in the
same S3 / broom / autoplot pipeline as the classical charts.shewhart_runs() implements the eight Nelson rules
(1984, 1985) plus a Western Electric “7 in a row” variant for backward
compatibility. Rule sets are user-configurable on every chart.shewhart_arl() performs Monte Carlo Average Run Length
simulation for arbitrary rule combinations.shewhart_box_cox() returns the profile log-likelihood,
optimal lambda, and 95% CI in the Box & Cox (1964) tradition.shewhart_diagnostics() produces a five-panel
Tukey-style residual diagnostic display.shewhart_capability() computes Cp/Cpk/Pp/Ppk with
bootstrap confidence intervals.calibrate() and monitor() provide an
explicit Phase I / Phase II workflow.shewhart_chart
with a specific subclass.print(), summary(),
autoplot(), tidy(), glance() and
augment() methods are provided for every chart type.locale
argument ("en", "pt", "es",
"fr") that controls plot labels and informative messages.
Validation errors remain in English to facilitate cross-user
debugging.Depends collapsed: the package no longer depends on the
entire tidyverse meta-package or on
tibbletime/pals/scales. The new
Imports are minimal and explicit.plotly moved to Suggests to avoid pulling
a heavy dependency for users who don’t need interactive plots.cli::cli_abort() /
cli::cli_warn() with multi-line, informative messages..onAttach() no longer prints a banner.data-raw/build_all.R script generates six synthetic
datasets (tablet_weight, bottle_fill,
pcb_solder, claims_p,
temperature_drift, bacterial_growth).pkgdown at
https://castlaboratory.github.io/shewhartr/. Ten topical articles,
including a dedicated memory-based-charts vignette covering
EWMA, CUSUM and the trade-offs versus Shewhart-style charts.shewhart() (the plotting function) has been removed.
Use shewhart_regression() followed by
autoplot().shewhart_fit() is no longer exported. Use
shewhart_regression().shewhart_model() is no longer exported. Use
shewhart_regression().shewhart_7points() is no longer exported. Use
shewhart_runs(rule = "we_seven_same") for the same
behaviour, or the recommended
shewhart_runs(rule = "nelson_2_nine_same").phase_rule = "we_seven_same" to recover the old
behaviour..onAttach() has been
removed.. (.fitted, .upper,
.lower, .flag_*).