[R-pkgs] New package stepR: fitting step-functions

[Thomas Hotz]

Dear R users,

It is my pleasure to announce the availability of package stepR (1.0-2) 
on CRAN.

The main purpose of the package is to fit piecewise constant functions 
(a.k.a. step-functions or block signals) to serial data in a fully 
data-driven manner under certain (Gaussian or non-Gaussian) 
distributional assumptions.

It mainly implements the algorithms described in the references below - 
in a (hopefully) user-friendly fashion.

Try

    library(stepR)
    example(smuceR) # for [1] and [2]
    example(jsmurf) # for [3]
    example(stepsel) # for [4]

to get an idea about what it can do, and how to use it.

We hope it proves useful; community feedback is therefore very welcome!

Best regards

Thomas Hotz
TU Ilmenau, Institute of Mathematics

References:

[1] Frick, K., Munk, A., and Sieling, H. (2014). Multiscale Change-Point 
Inference. With discussion and rejoinder by the authors. Journal of the 
Royal Statistical Society, Series B, 76(3), 495-580.
[2] Futschik, A., Hotz, T., Munk, A. Sieling, H. (2014). Multiresolution 
DNA partitioning: statistical evidence for segments. Bioinformatics,  
30(16), 2255-2262.
[3] Hotz, T., Schütte, O., Sieling, H., Polupanow, T., Diederichsen, U., 
Steinem, C., and Munk, A. (2013). Idealizing Ion Channel Recordings by a 
Jump Segmentation Multiresolution Filter. IEEE Transactions on 
NanoBioscience, 12(4), 376-386.
[4] Boysen, L., Kempe, A., Liebscher, V., Munk, A., Wittich, O. (2009). 
Consistencies and rates of convergence of jump-penalized least squares 
estimators. The Annals of Statistics, 37(1), 157-183.