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 | 
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