Package: SNSchart
Type: Package
Title: Sequential Normal Scores in Statistical Process Management
Version: 1.4.0
Authors@R: c(person("Victor", "Tercero", email = "victor.tercero@tec.mx", role=c("aut")),
  person("Luis", "Benavides", email = "luisbv@tec.mx", role = c("aut", "cre")),
  person("Jorge", "Merlo", email = "jorgemerlo24@gmail.com", role = c("ctb")))
Author: Victor Tercero [aut], Luis Benavides [aut, cre], Jorge Merlo
        [ctb]
Maintainer: Luis Benavides <luisbv@tec.mx>
Description: The methods discussed in this package are new
        non-parametric methods based on sequential normal scores 'SNS'
        (Conover et al (2017) <doi:10.1080/07474946.2017.1360091>),
        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. Some examples and more detail
        in 'SNS' is presented in the work by Conover et al (2019)
        <arXiv:1901.04443>.
Depends: R (>= 2.10)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: parallel, stats, MASS
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
Repository: https://luisbenavides.r-universe.dev
Date/Publication: 2021-04-05 23:33:01 UTC
RemoteUrl: https://github.com/luisbenavides/snschart
RemoteRef: HEAD
RemoteSha: c4133ae0d76cf0ead4c3f2a1f904e5644bccc80b
NeedsCompilation: no
Packaged: 2026-07-13 08:54:19 UTC; root