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PeakSegOptimal  

Optimal Segmentation Subject to Up-Down Constraints
View on CRAN: Click here


Download and install PeakSegOptimal package within the R console
Install from CRAN:
install.packages("PeakSegOptimal")

Install from Github:
library("remotes")
install_github("cran/PeakSegOptimal")

Install by package version:
library("remotes")
install_version("PeakSegOptimal", "2024.1.24")



Attach the package and use:
library("PeakSegOptimal")
Maintained by
Toby Dylan Hocking
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-21
Latest Update: 2018-05-25
Description:
Computes optimal changepoint models using the Poisson likelihood for non-negative count data, subject to the PeakSeg constraint: the first change must be up, second change down, third change up, etc. For more info about the models and algorithms, read "A log-linear time algorithm for constrained changepoint detection" by TD Hocking et al.
How to cite:
Toby Dylan Hocking (2017). PeakSegOptimal: Optimal Segmentation Subject to Up-Down Constraints. R package version 2024.1.24, https://cran.r-project.org/web/packages/PeakSegOptimal
Previous versions and publish date:
2017.06.20 (2017-06-21 19:13), 2017.07.11 (2017-07-11 23:28), 2017.07.12 (2017-07-12 21:42), 2018.05.25 (2018-05-25 17:50)
Other packages that cited PeakSegOptimal R package
View PeakSegOptimal citation profile
Other R packages that PeakSegOptimal depends, imports, suggests or enhances
Functions, R codes and Examples using the PeakSegOptimal R package
Some associated functions: H3K4me3_PGP_immune_chunk24 . H3K4me3_XJ_immune_chunk1 . PeakSegFPOP . PeakSegFPOPchrom . PeakSegPDPA . PeakSegPDPAInf . PeakSegPDPAchrom . PoissonLoss . oracleModelComplexity . 
Some associated R codes: PeakSegFPOP.R . PeakSegPDPA.R . PoissonLoss.R . oracle.R .  Full PeakSegOptimal package functions and examples
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