SNSchart Package"

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Install the package SNSchart hosted in github.

install_github("LuisBenavides/SNSchart")

Load the package

library("SNSchart")

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

Example 3.1.1.

Get dataset from Example 8.2 \code{example82} by @qiu_2013 (see Example 3.1.1 from @conover_etal_2019)

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

Table with the dataset using dataframe of \code{R} (first 10 rows).

knitr::kable(head(SNSchart::example82, 10))

Get the sns of the dataset

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

to plot it

plot(s)
X = SNSchart::example82$X #get the dataset into a data frame
X.id = SNSchart::example82$X.id
s = SNSchart::SNS(X=X,X.id=X.id)
plot(s)

CUSUM Variation to Detect a Change in Location

Example 3.2.1.

Get dataset from Example 8.4 \code{example84} by @qiu_2013 (see Example 3.2.1 from @conover_etal_2019)

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

Table with the dataset using dataframe of \code{R} (first 10 rows).

knitr::kable(head(SNSchart::example84, 10))

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)
X = SNSchart::example84$X #get the dataset into a data frame
X.id = SNSchart::example84$X.id
s = SNSchart::SNS(X=X,X.id=X.id, chart="CUSUM", chart.par=c(0.5, 4.389, 3)) 
plot(s)

EWMA Variation to Detect a Change in Location

Example 3.3.1.

Load package and get dataset from Example 8.4 \code{example84} by @qiu_2013 (Example 3.2.1 from @conover_etal_2019)

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

Table with the dataset using dataframe of \code{R} (first 10 rows).

knitr::kable(head(SNSchart::example84, 10))

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)
X = SNSchart::example84$X #get the dataset into a data frame
X.id = SNSchart::example84$X.id
s = SNSchart::SNS(X=X,X.id=X.id, chart="EWMA", chart.par=c(0.01, 2.0171))
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 \code{example87} by @qiu_2013 (Example 3.5.1 from @conover_etal_2019)

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

Table with the dataset using dataframe of \code{R} (first 10 rows).

knitr::kable(head(SNSchart::example87, 10))

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)
X = SNSchart::example87$X #get the dataset into a data frame
X.id = SNSchart::example87$X.id
Y = SNSchart::example87$Y
s = SNSchart::SNS(X=X,X.id=X.id, Y=Y, chart="EWMA", chart.par=c(0.01, 2.0171))
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 \code{example49} by @qiu_2013 (Example 4.3.1 from @conover_etal_2019)

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

Table with the dataset using dataframe of \code{R} (first 10 rows).

knitr::kable(head(SNSchart::example49, 10))

Get the SNS^2 of the dataset using a Shewhart scheme. In the example the reference sample is fixed therefore \code{isFixed=TRUE}.

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)
X = SNSchart::example49$X2
X.id = SNSchart::example49$X.id
Y = SNSchart::example49$Y2
s = SNSchart::SNS(X=X,X.id=X.id, Y=Y, chart="Shewhart", scoring="Z-SQ",isFixed = TRUE)
plot(s)

Multivariate Sequential Normal Scores to Detect a Change in Location

Example 6.1.1.

Get dataset from Example 9.1 \code{example91} by @qiu_2013 (see Example 6.1.1 from @conover_etal_2019).

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

Table with the dataset using dataframe of \code{R} (first 10 rows).

knitr::kable(head(SNSchart::example91, 10))

Get the multivariate sequential normal scores

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

and plot it

plot(msns)
X = SNSchart::example91[,1:2] #get the dataset into a data frame
X.id = SNSchart::example91$X.id
msns = SNSchart::MSNS(X, X.id)
plot(msns)

Multivariate Sequential Normal Scores to Detect a Change in Location

Example 6.2.1.

Get dataset from Example 9.3 \code{example93} by @qiu_2013 (see Example 6.2.1 from @conover_etal_2019).

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

Table with the dataset using dataframe of \code{R} (first 10 rows).

knitr::kable(head(SNSchart::example93, 10))

Get the multivariate sequential normal scores. Null distribution considered is the \code{F} statistic.

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

and plot it

plot(msns)
X = SNSchart::example93[,1:2] #get the dataset into a data frame
X.id = SNSchart::example93$X.id
msns = SNSchart::MSNS(X, X.id, null.dist = "F")
plot(msns)

References



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SNSchart documentation built on April 7, 2021, 9:07 a.m.