mosum: A Package for Moving Sums in Change-Point Analysis
Dublin Core
Title
mosum: A Package for Moving Sums in Change-Point Analysis
Subject
MOSUM, change-point analysis, time series
Description
Time series data, i.e., temporally ordered data, is routinely collected and analysed
in in many fields of natural science, economy, technology and medicine, where it is of
importance to verify the assumption of stochastic stationarity prior to modeling the data.
Nonstationarities in the data are often attributed to structural changes with segments between adjacent change-points being approximately stationary. A particularly important,
and thus widely studied, problem in statistics and signal processing is to detect changes
in the mean at unknown time points. In this paper, we present the R package mosum,
which implements elegant and mathematically well-justified procedures for the multiple
mean change problem using the moving sum statistics
in in many fields of natural science, economy, technology and medicine, where it is of
importance to verify the assumption of stochastic stationarity prior to modeling the data.
Nonstationarities in the data are often attributed to structural changes with segments between adjacent change-points being approximately stationary. A particularly important,
and thus widely studied, problem in statistics and signal processing is to detect changes
in the mean at unknown time points. In this paper, we present the R package mosum,
which implements elegant and mathematically well-justified procedures for the multiple
mean change problem using the moving sum statistics
Creator
Alexander Meier
Source
https://www.jstatsoft.org/article/view/v097i08
Publisher
Otto von Guericke
University Magdeburg
University Magdeburg
Date
Januari 2021
Contributor
Fajar bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Alexander Meier, “mosum: A Package for Moving Sums in Change-Point Analysis,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8183.