rsp {dfphase1} | R Documentation |
rsp
implements the Phase I method described in Capizzi and Masarotto (2013).
rsp(y, plot = TRUE, L = 1000, seed = 11642257, alpha = 0.05, maxsteps = min(50, round(NROW(y)/15)), lmin = max(5, min(10, round(NROW(y)/10))))
y |
Phase I data; |
plot |
logical; if |
L |
integer; the number of random permutations used to compute the p-values. |
seed |
positive integer; if not |
alpha |
real; the significance level used to compute the level and scale
estimates; if one of the p-values is greater than
|
maxsteps |
integer; the maximum number of step shifts which the procedure tries to detect. |
lmin |
integer; the minimum length of a step. |
A list with elements
p |
the adjusted p-values |
stat |
the summary statistics (a mx2 matrix) |
fitted |
the (possibly time-variant) estimates of the process level and scale (a mx2 matrix). |
Giovanna Capizzi and Guido Masarotto.
G. Capizzi, G. Masarotto (2013), “Phase I Distribution-Free Analysis of Univariate Data”. Journal of Quality Technology, 45, pp. 273-284.
# Individual observations with a transient level change set.seed(112233) level <- c(rep(0,20),rep(3,10),rep(0,20)) x <- level+rt(50,4) rsp(x) # Individual observations with a scale step change scale <- c(rep(1,25),rep(3,25)) x <- scale*rt(50,4) rsp(x) data(fe) rsp(fe) data(colonscopy) rsp(colonscopy)