Copyright: This package is Copyright (C) 2005-2014 Weierstrass

Description: Collection of R-functions implementing the
described in "J. Polzehl and V. Spokoiny (2006)
and "J. Polzehl and V. Spokoiny (2004) <DOI:10.20347/WIAS.PREPRINT.998>".
Copyright: This package is Copyright (C) 2005-2016 Weierstrass

Depends: R (>= 3.2.0), methods, awsMethods (>= 1.0-1), gsl
Description: We provide a collection of R-functions implementing
adaptive smoothing procedures in 1D, 2D and 3D. This includes the
"J. Polzehl and V. Spokoiny (2004) <DOI:10.20347/WIAS.PREPRINT.998>"
and "J. Polzehl, K. Papafitsoros, K. Tabelow (2018) <DOI:10.20347/WIAS.PREPRINT.2520>",
the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter.
Copyright: This package is Copyright (C) 2005-2018 Weierstrass

Depends: R (>= 3.4.0), methods, awsMethods (>= 1.0-1), gsl

Copyright: This package is Copyright (C) 2005-2019 Weierstrass

Usage of the package is also described in
Magnetic Resonance Brain Imaging, Appendix A, Springer, Use R! Series.

Copyright: This package is Copyright (C) 2005-2020 Weierstrass

Propagation-Separation Approach to adaptive smoothing,
The package is described in detail in Polzehl J, Papafitsoros K, Tabelow K (2020).
Patch-Wise Adaptive Weights Smoothing in R. Journal of Statistical Software, 95(6), 1-27.
Usage of the package in neuroimaging is illustrated in Polzehl and Tabelow (2019),

Usage of the package in MR imaging is illustrated in Polzehl and Tabelow (2019),

Title: Client for the Amazon Alexa Web Information Services API
Authors@R: c(person("Gaurav", "Sood", email = "gsood07@gmail.com", role = c("aut", "cre")),
person("Thomas", "Leeper", email = "thosjleeper@gmail.com", role = "ctb"))
Description: Use the Amazon Alexa Web Information Services API to
find information about domains, including the kind of content
that they carry, how popular are they---rank and traffic history,
sites linking to them, among other things. See <https://aws.amazon.com/awis/>

Imports: httr, aws.signature, xml2, dplyr