npcp: Some Nonparametric CUSUM Tests for Change-Point Detection in
Possibly Multivariate Observations
Provides nonparametric CUSUM tests for detecting changes
in possibly serially dependent univariate or low-dimensional
multivariate observations. Retrospective tests sensitive to changes
in the expectation, the variance, the covariance, the
autocovariance, the distribution function, Spearman's rho, Kendall's
tau, Gini's mean difference, and the copula are provided, as well as
a test for detecting changes in the distribution of independent
block maxima (with environmental studies in mind). The package also
contains a test sensitive to changes in the autocopula and a
combined test of stationarity sensitive to changes in the
distribution function and the autocopula. The latest additions are
an open-end sequential test based on the retrospective CUSUM
statistic that can be used for monitoring changes in the mean of
possibly serially dependent univariate observations, as well as
closed-end and open-end sequential tests based on empirical
distribution functions that can be used for monitoring changes in
the contemporary distribution of possibly serially dependent
univariate or low-dimensional multivariate observations.
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=npcp
to link to this page.
[aut, cre],
Alex Verhoijsen