Title: Forgetting Factor Methods for Change Detection in Streaming Data
Description: An implementation of the adaptive forgetting factor scheme described in Bodenham and Adams (2016) <doi:10.1007/s11222-016-9684-8> which adaptively estimates the mean and variance of a stream in order to detect multiple changepoints in streaming data. The implementation is in C++ and uses Rcpp. Additionally, implementations of the fixed forgetting factor scheme from the same paper, as well as the classic CUSUM and EWMA methods, are included.

Suggests: testthat (>= 1.0.2), knitr, rmarkdown

Description: Provides a simple and efficient wrapper around the fastest
Fourier transform in the west (FFTW) library.
Author: Sebastian Krey <skrey@statistik.tu-dortmund.de> Uwe Ligges

Title: Fast FFT and DCT Based on the FFTW Library
Fourier transform in the west (FFTW) <http://www.fftw.org/> library.
Authors@R: c( person("Olaf", "Mersmann", email="olafm@p-value.net",

Fourier transform in the west (FFTW) library <http://www.fftw.org/>.

Description: This package is a wrapper for certain fftw functions.
Please see the fftw package for additional tools. This package
provides access to the two-dimensional fft, the multivariate
fft, and the one-dimensional real to complex fft using fftw3.
The fft functions can be specified to not return the Hermitian
conjugate of real data, and both the one-dimensional and
multivariate fft functions can be inverted without the
Hermitian conjugate. Please see the package fftw for general
one-dimensional use of fftw, the discrete cosine transform, and
for more detailed use of performancing enhancing plans when

Title: Wrapper for 'FFTW3' Includes: One-Dimensional, Two-Dimensional,
SystemRequirements: fftw3 (libfftw3-dev (deb), or fftw-devel (rpm))
Description: Provides a wrapper for several 'FFTW' functions. This package provides access to the two-dimensional 'FFT', the multivariate 'FFT', and the one-dimensional real to complex 'FFT' using the 'FFTW3' library. The package includes the functions fftw() and mvfftw() which are designed to mimic the functionality of the R functions fft() and mvfft(). The 'FFT' functions have a parameter that allows them to not return the redundant complex conjugate when the input is real data.