vMask.method3: Method 3 for V-Mask Implementation: Using mu0, k, alpha and...

In vMask: Detect Small Changes in Process Mean using CUSUM Control Chart by v-Mask

Description

The V-mask method in vMask Package, is considered on the basis of variety of situations/information by different functions. One of these functions is vMask.method1 which can plot the V-mask based on μ_0, k and the probabilities of type I and II errors of testing null hypotheses H_0: μ = μ_0 vs. alternative hypothesis H_1: μ = μ_0 + k σ.

Usage

vMask.method3(data, mu0 = mean(data), k = .5*sd(data), alpha, beta = 0.001, sleep = 1)

Arguments

data	Type of inputted data must be a matrix with dim=c(m,n), in which m is size of samples and n is size of each subsample. Meanwhile, data can be a numerical vector where its elements are sub-sample means.
mu0	The target value for process mean, with default mean(data).
k	With default 0.5 σ and it depends on the form of the alternative hypothesis H_1: μ = μ_1\ (μ_1=μ_0+k σ).
alpha	The probability of type I error in testing hypotheses H_0: μ = μ_0 vs. H_1: μ = μ_0 + k σ.
beta	The probability of type II error in testing hypotheses H_0: μ = μ_0 vs. H_1: μ = μ_0 + k σ. The default of beta is the very small probability value 0.001.
sleep	Sleeping time (in second) of the program between showing figures. This time needs for see the result of checking i-th point on CUSUM control chart by V-mask. Also, if sleep="PressEnter", then the user must press key [Enter] in 'R Console' window to continue/check the next cumulative summation point on chart with V-mask.

Value

d	The distance between two following points: (1) O, i.e the latest cumulative sum point (which duty of the V-mask is checking this point), and (2) P, i.e. the junction points of V-mask arms.
theta	half of the angle formed by the V-mask arms (in degrees).
h	the vertical distance between the origin and the upper (or lower) arm of V-mask.
c	A vector of the cumulative differences between statistic (mean) values and the mean target value; i.e. c=(c_1, ..., c_m) where c_i=∑_{j=1}^{i} (\bar{x}_j - μ_0) .
OutControl	The number of Out-of-control points in CUSUM chart.
InControl	The number of In-control points in CUSUM chart.

See Also

vMask.method5

Examples

m = 26	#The size of samples
n = 2 	#The size of each subsample
set.seed(2345)
Data = matrix(rnorm(m*n, 0,1), nrow=m)
head(Data)

vMask.method3( data=Data, k=1, alpha=.1, beta=.01, s=0 )
vMask.method3( data=Data, k=1, alpha=.2, beta=.01, s=0 )    #Compare with the previous line
vMask.method3( data=Data, k=1, alpha=.2, s=0 )		    #Result is same, by default beta=.001

vMask documentation built on May 1, 2019, 10:21 p.m.