LuisBenavides/SNS.test: Sequential Normal Scores in Statistical Process Management for testing

The methods discussed in this paper are new nonparametric methods based on sequential normal scores (SNS), designed for sequences of observations, usually time series data, which may occur singly or in batches, and may be univariate or multivariate. These methods are designed to detect changes in the process, which may occur as changes in location (mean or median), changes in scale (standard deviation, or variance), or other changes of interest in the distribution of the observations, over the time observed. They usually apply to large data sets, so computations need to be simple enough to be done in a reasonable time on a computer, and easily updated as each new observation (or batch of observations) becomes available.

Getting started

Package details

AuthorVictor Tercero [aut], Luis Benavides [aut, cre], Jorge Merlo [ctb]
MaintainerLuis Benavides <luisbv@tec.mx>
LicenseMIT + file LICENSE
Version1.4.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("LuisBenavides/SNS.test")
LuisBenavides/SNS.test documentation built on June 25, 2022, 11:52 p.m.