IDetect: Isolate-Detect Methodology for Multiple Change-Point Detection
Provides efficient implementation of the Isolate-Detect
methodology for the consistent estimation of the number and location of multiple
change-points in one-dimensional data sequences from the "deterministic
+ noise" model. For details on the Isolate-Detect methodology, please see Anastasiou and
Fryzlewicz (2018) <https://docs.wixstatic.com/ugd/24cdcc_6a0866c574654163b8255e272bc0001b.pdf>.
Currently implemented scenarios are: piecewise-constant signal with Gaussian
noise, piecewise-constant signal with heavy-tailed noise, continuous piecewise-linear
signal with Gaussian noise, continuous piecewise-linear signal with heavy-tailed noise.
Version: |
0.1.0 |
Depends: |
R (≥ 3.3.0) |
Imports: |
splines |
Suggests: |
testthat |
Published: |
2018-03-09 |
Author: |
Andreas Anastasiou [aut, cre],
Piotr Fryzlewicz [aut] |
Maintainer: |
Andreas Anastasiou <a.anastasiou at lse.ac.uk> |
License: |
GPL-3 |
NeedsCompilation: |
no |
Citation: |
IDetect citation info |
CRAN checks: |
IDetect results |
Documentation:
Downloads:
Reverse dependencies:
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