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EATME  

Exponentially Weighted Moving Average with Adjustments to Measurement Error
View on CRAN: Click here


Download and install EATME package within the R console
Install from CRAN:
install.packages("EATME")

Install from Github:
library("remotes")
install_github("cran/EATME")

Install by package version:
library("remotes")
install_version("EATME", "0.1.0")



Attach the package and use:
library("EATME")
Maintained by
Cheng-Kuan Lin Developer
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-17
Latest Update: 2022-05-17
Description:
The univariate statistical quality control tool aims to address measurement error effects when constructing exponentially weighted moving average p control charts. The method primarily focuses on binary random variables, but it can be applied to any continuous random variables by using sign statistic to transform them to discrete ones. With the correction of measurement error effects, we can obtain the corrected control limits of exponentially weighted moving average p control chart and reasonably adjusted exponentially weighted moving average p control charts. The methods in this package can be found in some relevant references, such as Chen and Yang (2022) ; Yang et al. (2011) ; Yang and Arnold (2014) ; Yang (2016) and Yang and Arnold (2016) .
How to cite:
Cheng-Kuan Lin Developer (2022). EATME: Exponentially Weighted Moving Average with Adjustments to Measurement Error. R package version 0.1.0, https://cran.r-project.org/web/packages/EATME. Accessed 31 Jan. 2025.
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