The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
rbcc implements risk-based statistical process control
charts in the presence of measurement uncertainty. The package compares
the process state obtained from reference values with the decision
obtained from measured values, accounts for all four decision outcomes,
and can select chart limits by minimizing their total cost.
rbcc() and
rbcc_opt()rbmacc() and
rbmacc_opt()rbewmacc() and
rbewmacc_opt()rbcusumcc() and
rbcusumcc_opt()rbmcc() and
rbmcc_opt()The default exact threshold optimizer exploits the piecewise-constant structure of the empirical decision cost and is deterministic. Bounded numerical optimization and sequential or optional parallel grid search remain available.
After installation, open the complete workflow with:
vignette("rbcc-workflow", package = "rbcc")A minimal example is:
library(rbcc)
set.seed(42)
X <- rnorm(80, mean = 10, sd = 0.5)
UC <- rnorm(80, mean = 0, sd = 0.05)
C <- c(c11 = 1, c10 = 5, c01 = 60, c00 = 5)
fit <- rbcc_opt(X, UC, C, n = 1, type = "xbar")
print(fit)
s <- summary(fit) # no console output during assignment
s$cost0
p <- plot(fit) # no drawing during assignment
p # draws the ggplot objectfit_grid <- rbcc_opt(
X, UC, C,
optimizer = "grid",
parallel = FALSE,
control = rbcc_control(grid_size = 401)
)For sufficiently large grid problems, evaluation can be distributed across workers:
fit_parallel <- rbcc_opt(
X, UC, C,
optimizer = "grid",
parallel = TRUE,
workers = 2,
control = rbcc_control(grid_size = 2001)
)Parallel startup and data-transfer overhead can dominate small problems; the exact optimizer remains the recommended default for scalar empirical limits.
See citation("rbcc") for the methodological
publications.
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.
Health stats visible at Monitor.