cusumPfaCed | R Documentation |
Compute the Probability of False Alarm, PFA, and the Conditional Expected Delay, CED, for the Normal, Binomial and Poisson distributions
cusumPfaCedBinom(size0 = 0, prob0 = 1, size1 = 0, prob1 = 1, tau = 10, N = 100, limit = 10000, seed = NA, kp = 1, km = -1, hp = 3, hm = -3, side = "both", printSummary = TRUE) cusumPfaCedNorm(mean0 = 0, sd0=1, mean1=0, sd1=1, tau=10, N=100, limit=10000, seed=NA, kp=1, km=-1, hp=3, hm=-3, side="both", printSummary = TRUE) cusumPfaCedPois(lambda0 = 0, lambda1=1, tau=10, N=100, limit=10000, seed=NA, kp=1, km=-1, hp=3, hm=-3, side="both", printSummary = TRUE)
size0 |
number of trials (zero or more) |
prob0 |
probability of success on each trial |
size1 |
number of trials (zero or more) after a process level change |
prob1 |
probability of success on each trial after a process level change |
mean0 |
distribution mean |
sd0 |
distribution standard deviation |
mean1 |
distribution mean after a process level change |
sd1 |
distribution standard deviation after a process level change |
lambda0 |
(non-negative) mean |
lambda1 |
(non-negative) mean after a process level change |
tau |
time on which the process level change occurs |
N |
the number of replicates |
limit |
safety parameter, stop rule for procedures with very long ARL |
seed |
a single value, interpreted as an integer. If specified make the simulation replicable. |
kp |
K^+ parameter of the control scheme |
km |
K^- parameter of the control scheme |
hp |
h^+ parameter of the control scheme |
hm |
h^- parameter of the control scheme |
side |
a character string specifying the side of the control scheme, must be one of "both" (default), "upper" or "lower" |
printSummary |
logical, if |
a list with elements:
rls |
a numeric vector representing the Run Length of the simulation |
statistics |
a numeric vector with summary statistics |
run |
a list of length |
Daniele Amberti
Kenett, R., Zacks, S. with contributions by Amberti, D. Modern Industrial Statistics: with applications in R, MINITAB and JMP. Wiley.
cusumPfaCedNorm(mean1=1.5, tau=100, N=100, limit=1000, seed=123)
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