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.

SNSchart Package

Luis Benavides

2021-04-05

Using Sequential Normal Scores to Detect a Change in Location (Shewhart Scheme)

Example 3.1.1.

Get dataset from Example 8.2 by Qiu (2013) (see Example 3.1.1 from Conover, Tercero, and Cordero-Franco (2019))

X = SNSchart::example82$X
X.id = SNSchart::example82$X.id

Table with the dataset using dataframe of (first 10 rows).

X	X.id
-0.623	1
-1.068	1
0.605	1
-0.002	1
-0.807	1
-0.105	2
-0.037	2
-0.595	2
1.222	2
-0.545	2

Get the sns of the dataset

s = SNSchart::SNS(X=X,X.id=X.id)

to plot it

plot(s)

CUSUM Variation to Detect a Change in Location

Example 3.2.1.

Get dataset from Example 8.4 by Qiu (2013) (see Example 3.2.1 from Conover, Tercero, and Cordero-Franco (2019))

X = SNSchart::example84$X
X.id = SNSchart::example84$X.id

Table with the dataset using dataframe of (first 10 rows).

X	X.id
-0.393	1
-0.685	1
0.360	1
0.148	1
0.867	1
-0.552	2
-0.462	2
-0.979	2
-0.580	2
-0.008	2

Get the sns of the dataset using a CUSUM scheme

s = SNSchart::SNS(X=X,X.id=X.id, chart="CUSUM", chart.par=c(0.5, 4.389, 3))

to plot it

plot(s)

EWMA Variation to Detect a Change in Location

Example 3.3.1.

Load package and get dataset from Example 8.4 by Qiu (2013) (Example 3.2.1 from Conover, Tercero, and Cordero-Franco (2019))

X = SNSchart::example84$X
X.id = SNSchart::example84$X.id

Table with the dataset using dataframe of (first 10 rows).

X	X.id
-0.393	1
-0.685	1
0.360	1
0.148	1
0.867	1
-0.552	2
-0.462	2
-0.979	2
-0.580	2
-0.008	2

Get the sns of the dataset using a EWMA scheme

s = SNSchart::SNS(X=X,X.id=X.id, chart="EWMA", chart.par=c(0.01, 2.0171))

to plot it

plot(s)

Sequential Normal Scores with a Reference Data Set (Phase 1)

Example 3.5.1.

Load package and get dataset from Example 8.7 by Qiu (2013) (Example 3.5.1 from Conover, Tercero, and Cordero-Franco (2019))

X = SNSchart::example87$X
X.id = SNSchart::example87$X.id
Y = SNSchart::example87$Y

Table with the dataset using dataframe of (first 10 rows).

X	X.id	Y
-0.034	1	-0.333
-0.103	2	-0.039
0.463	3	0.071
0.193	4	-0.303
0.723	5	-0.712
1.362	6	0.294
-0.366	7	-0.421
-0.610	8	-0.241
0.012	9	0.740
0.269	10	0.534

Get the sns of the dataset using a EWMA scheme

s = SNSchart::SNS(X=X,X.id=X.id, Y=Y, chart="EWMA", chart.par=c(0.01, 2.0171))

to plot it

plot(s)

Detecting a Change in Both Location and Scale (SNS Method)

Example 4.3.1

Load package and get dataset from Example 4.9 by Qiu (2013) (Example 4.3.1 from Conover, Tercero, and Cordero-Franco (2019))

X = example49$X2
X.id = example49$X.id
Y = example49$Y2

Table with the dataset using dataframe of (first 10 rows).

X1	X2	Y1	Y2	X.id
0.5993625	-0.7822084	0.0187462	-0.7618043	1
0.6654434	-0.4997350	-0.1842525	0.4193754	1
2.3679540	2.3102095	-1.3713305	-1.0399434	1
3.1377671	-1.7294545	-0.5991677	0.7115740	1
1.5058193	-1.7333567	0.2945451	-0.6332130	1
1.7863424	-4.6420341	0.3897943	0.5631747	2
0.0977881	1.2176603	-1.2080762	0.6609867	2
1.5328970	2.3000121	-0.3636760	-1.6580509	2
0.3541057	-2.3991953	-1.6266727	1.0281680	2
1.2909875	-3.1600015	-0.2564784	1.1279536	2

Get the SNS^2 of the dataset using a Shewhart scheme. In the example the reference sample is fixed therefore .

s = SNSchart::SNS(X=X,X.id=X.id, Y=Y, chart="Shewhart", scoring="Z-SQ",isFixed = TRUE)

to plot it. Only the plot of the monitoring sample is presented.

plot(s)

Multivariate Sequential Normal Scores to Detect a Change in Location

Example 6.1.1.

Get dataset from Example 9.1 by Qiu (2013) (see Example 6.1.1 from Conover, Tercero, and Cordero-Franco (2019)).

X = SNSchart::example91[,1:2]
X.id = SNSchart::example91$X.id

Table with the dataset using dataframe of (first 10 rows).

X1	X2	X.id
-0.692	-1.230	1
0.165	0.267	1
-0.153	-0.325	1
0.289	-1.325	1
0.140	0.211	1
0.188	-0.236	1
0.072	2.337	1
0.685	0.614	1
-1.245	-1.013	1
-0.153	0.189	1

Get the multivariate sequential normal scores

msns = SNSchart::MSNS(X, X.id)

and plot it

plot(msns)

Multivariate Sequential Normal Scores to Detect a Change in Location

Example 6.2.1.

Get dataset from Example 9.3 by Qiu (2013) (see Example 6.2.1 from Conover, Tercero, and Cordero-Franco (2019)).

X = SNSchart::example93[,1:2]
X.id = SNSchart::example93$X.id

Table with the dataset using dataframe of (first 10 rows).

X1	X2	X.id
-1.197	-1.060	1
-0.536	-0.447	1
1.302	1.826	1
-0.449	0.933	1
-2.569	-2.584	1
-0.805	-0.594	1
-0.584	-0.069	1
-1.635	-2.966	1
1.679	-1.278	1
-0.122	0.274	1

Get the multivariate sequential normal scores. Null distribution considered is the statistic.

msns = SNSchart::MSNS(X, X.id, null.dist = "F")

and plot it

plot(msns)

References

Conover, W. J., Victor G. Tercero, and Alvaro E. Cordero-Franco. 2019. “An Approach to Statistical Process Control That Is New, Nonparametric, Simple, and Powerful.” arXiv Preprint arXiv:1901.04443.

Qiu, Peihua. 2013. Introduction to Statistical Process Control. Chapman; Hall/CRC.

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.