Package: FluxPoint
Type: Package
Title: Change Point Detection for Non-Stationary and Cross-Correlated
        Time Series
Version: 0.1.2
Authors@R: c(
    person("Yuhan", "Tian",
           email = "yuhan.tian@fau.de",
           role = c("aut", "cre")),
    person("Abolfazl", "Safikhani",
           email = "asafikha@gmu.edu",
           role = "aut")
           )
Maintainer: Yuhan Tian <yuhan.tian@fau.de>
Description: Implements methods for multiple change point detection in multivariate
    time series with non-stationary dynamics and cross-correlations. The methodology
    is based on a model in which each component has a fluctuating mean represented by
    a random walk with occasional abrupt shifts, combined with a stationary vector
    autoregressive structure to capture temporal and cross-sectional dependence. The
    framework is broadly applicable to correlated multivariate sequences in which
    large, sudden shifts occur in all or subsets of components and are the primary
    targets of interest, whereas small, smooth fluctuations are not. Although random
    walks are used as a modeling device, they provide a flexible approximation for a
    wide class of slowly varying or locally smooth dynamics, enabling robust
    performance beyond the strict random walk setting.
License: GPL-2
Encoding: UTF-8
Imports: blockmatrix, corpcor, doParallel, ggplot2, glmnet, MASS,
        Matrix, nnls, pracma, SimDesign
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-01-10 11:58:37 UTC; AAA
Author: Yuhan Tian [aut, cre],
  Abolfazl Safikhani [aut]
Repository: CRAN
Date/Publication: 2026-01-10 14:40:20 UTC
Built: R 4.6.0; ; 2026-04-29 02:50:34 UTC; unix
