mphase1 {dfphase1} | R Documentation |
Distribution-free Phase I analysis of multivariate data
Description
Retrospective change point detection using the method described by Capizzi and Masarotto (2017).
Usage
mphase1(x, plot = TRUE, post.signal = TRUE, isolated = dim(x)[2] > 1, step = TRUE,
alpha = 0.05, gamma = 0.5, K = min(50, round(sqrt(dim(x)[3]))),
lmin = 5, L = 1000, seed = 11642257)
Arguments
x |
a pxnxm array containing the observations; |
plot |
logical; if |
post.signal |
logical; if |
isolated |
logical; if |
step |
logical; if |
alpha |
real; the acceptable false alarm probability; if the
observed p-value is greater than |
gamma |
real; the extra penalization for the extended BIC criteria. |
K |
integer; the maximum number of shifts which the procedure tries to detect. |
lmin |
integer; the minimum length of a step shift. |
L |
integer; the number of random permutations used to compute the p-values. |
seed |
integer; if not |
Value
Functions mphase1
returns an object of class mphase1
containing
p.value |
The p-value. |
Wobs |
The overall test statistic. |
alasso |
A data-frame containing the result of the post-signal diagnosis analysis,i.e., the times and types of shifts and the involved variables identified using the adaptive LASSO. |
forward |
A data frame containing the result of the forward search analysis, i.e., the times and types of the possible shifts as well as the elementary test statistics and the estimates of their (conditional) means and standard deviations. |
center , scatter |
The location vector and dispersion matrix used to standardize the original data. |
signed.ranks |
A pxnxm array containing the signed ranks. |
fitted , residuals |
Two pxnxm arrays containing the fitted means and the residuals, i.e., the difference between the observations and the fitted values. |
Author(s)
Giovanna Capizzi and Guido Masarotto.
References
G. Capizzi and G. Masarotto (2017), Phase I Distribution-Free Analysis of Multivariate Data, Technometrics, 59, pp. 484–495, doi:10.1080/00401706.2016.1272494.
See Also
Examples
# A simulated in-control data from a Student's t distribution
# with 3 degrees of freedom
set.seed(123)
x <- sweep(array(rnorm(5*5*50),c(5,5,50)),c(2,3),sqrt(rchisq(5*50,3)/3),"/")
mphase1(x)
# Reproduction of the two examples given in Capizzi and Masarotto (2016)
data(ryan)
mphase1(ryan)
data(gravel)
mphase1(gravel)