Title: Nonparametric Extended Median Test - Cumulative Summation Method
Version: 0.0.1.0
Description: Calculates a cumulative summation nonparametric extended median test based on the work of Brown & Schaffer (2020) <doi:10.1080/03610926.2020.1738492>. It then generates a control chart to assess processes and determine if any streams are out of control.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.2.1
URL: https://github.com/calebgreski/nemtr
BugReports: https://github.com/calebgreski/nemtr/issues
Imports: magrittr, tidyr, dplyr, ggplot2
Suggests: testthat
Depends: R (≥ 3.50)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2023-01-18 01:45:07 UTC; caleb
Author: Caleb Greski [aut, cre], Austin Brown [aut]
Maintainer: Caleb Greski <caleb.p@greski.com>
Repository: CRAN
Date/Publication: 2023-01-18 12:10:02 UTC

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

lhs

A value or the magrittr placeholder.

rhs

A function call using the magrittr semantics.

Value

The result of calling rhs(lhs).


Read and Validate Dataframe

Description

Read in data and validate before analysis is conducted

Usage

dataRead(
  dataFrame,
  timing,
  streams,
  VoI = NA,
  type = "long",
  median0 = NA,
  delta = 3
)

Arguments

dataFrame

A user inputted dataframe, can be wide or long

timing

A string of the timing variable name

streams

A string of the streams variable name

VoI

A string of the Variable of Interest name

type

A string of the type of data (default long)

median0

A value for expected median

delta

A value for delta (default 3)

Value

A validated dataframe in long format

Examples

set.seed(795014178)
streams <- 20
time <- 60
samples <- 15
mu0 <- 3
delta <- 3
library(dplyr)
turnstiles <- tibble(
  turnstile = rep(rep(1:streams,each=samples),time),
  hour = rep(1:time,each=streams * samples),
  sample = rep(rep(1:samples), times = streams * time),
  waitTime = rexp(streams * time * samples,rate=.22985)
  ) %>% mutate(waitTime = if_else(hour == 38, waitTime * 2,waitTime))
dataRead(turnstiles, timing="hour", streams="sample", VoI="waitTime", type="long", median0 = 3)


Nonparametric Extended Median Test

Description

Take a dataframe, validate it, and then conduct the Nonparametric Extended Median Test to generate and display a control chart

Usage

nemtr(
  dataFrame,
  timing,
  streams,
  VoI = NA,
  type = "long",
  median0 = NA,
  delta = 3
)

Arguments

dataFrame

A user inputted dataframe, can be wide or long

timing

A string of the timing variable name

streams

A string of the streams variable name

VoI

A string of the Variable of Interest name

type

A string of the type of data (default long)

median0

A value for expected median

delta

A value for delta (default 3)

Value

A validated dataframe in long format

Examples

set.seed(795014178)
streams <- 20
time <- 60
samples <- 15
mu0 <- 3
delta <- 3
library(dplyr)
turnstiles <- tibble(
  turnstile = rep(rep(1:streams,each=samples),time),
  hour = rep(1:time,each=streams * samples),
  sample = rep(rep(1:samples), times = streams * time),
  waitTime = rexp(streams * time * samples,rate=.22985)
  ) %>% mutate(waitTime = if_else(hour == 38, waitTime * 2,waitTime))
nemtr(turnstiles, timing="hour", streams="sample", VoI="waitTime", type="long", median0 = 3)