CRAN/E | fastcpd

fastcpd

Fast Change Point Detection via Sequential Gradient Descent

Installation

About

Implements fast change point detection algorithm based on the paper "Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis" by Xianyang Zhang, Trisha Dawn . The algorithm is based on dynamic programming with pruning and sequential gradient descent. It is able to detect change points a magnitude faster than the vanilla Pruned Exact Linear Time(PELT). The package includes examples of linear regression, logistic regression, Poisson regression, penalized linear regression data, and whole lot more examples with custom cost function in case the user wants to use their own cost function.

Citation fastcpd citation info
fastcpd.xingchi.li
github.com/doccstat/fastcpd
Bug report File report

Key Metrics

Version 0.14.3
R ≥ 2.10
Published 2024-04-26 3 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks fastcpd results

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Maintainer

Maintainer

Xingchi Li

anthony.li@stat.tamu.edu

Authors

Xingchi Li

aut / cre / cph

Xianyang Zhang

aut / cph

Material

README
NEWS
Reference manual
Package source

In Views

TimeSeries

Vignettes

Comparison with other R packages
Comparison with vanilla PELT
Advanced examples
Custom logistic regression model

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

fastcpd archive

Depends

R ≥ 2.10

Imports

fastglm
forecast
glmnet
Matrix
methods
Rcpp ≥ 0.11.0
stats
tseries

Suggests

abind
breakfast
changepoint
cpm
CptNonPar
dplyr
fpop
ggplot2
gridExtra
jointseg
knitr
lubridate
matrixStats
mockthat
mvtnorm
not
numDeriv
RcppClock
reshape2
rmarkdown
segmented
stepR
testthat ≥ 3.0.0
VARDetect
wbs
xml2
zoo

LinkingTo

progress
Rcpp
RcppArmadillo
RcppClock
testthat