Title: Simulate Keyboard Press and Mouse Click
Description: Control your keyboard and mouse with R code, simulate key press and mouse click.

Title: Keyboard and Mouse Input Simulation for Windows OS
Authors@R: c(person("Jim", "Chen", role = c("aut", "cre"), email = "jim71183@gmail.com"),
person("Jeff", "Keller", role = c("aut", "ctb"), email = "github@vtkellers.com"),
person("Chieh", "Hsu", role = c("ctb"), email = "tiff103012345@gmail.com"))
Description: Control your keyboard and mouse with R code by simulating key presses and mouse clicks. The input simulation is implemented with the Windows API.

person("Garry", "Hopwood", role = c("ctb"), email = "garryhopwood@hotmail.com"),

Title: Data on House Sales in King County WA
Description: Data on houses in and around Seattle WA are included. Basic
characteristics are given along with sale prices.
Author: Max Kuhn [aut, cre] (<https://orcid.org/0000-0003-2402-136X>)

Package: Kmedians
Type: Package
Title: K-Medians
Version: 0.1.0
Authors@R: c(person("Antoine","Godichon-Baggioni", role = c("aut", "cre","cph"),
email = "antoine.godichon_baggioni@upmc.fr"),
person("Sobihan","Surendran", role = "aut") )
Description: Online, Semi-online, and Offline K-medians algorithms are
given. For both methods, the algorithms can be initialized
randomly or with the help of a robust hierarchical
clustering. The number of clusters can be selected with the
help of a penalized criterion. We provide functions to provide
robust clustering. Function gen_K() enables to generate a sample
of data following a contaminated Gaussian mixture.
Functions Kmedians() and Kmeans() consists in a K-median and a
K-means algorithms while Kplot() enables to produce graph for both
methods.
Cardot, H., Cenac, P. and Zitt, P-A. (2013). "Efficient and fast estimation of the geometric median in Hilbert spaces with an averaged stochastic gradient algorithm". Bernoulli, 19, 18-43. <doi:10.3150/11-BEJ390>.
Cardot, H. and Godichon-Baggioni, A. (2017). "Fast Estimation of the Median Covariation Matrix with Application to Online Robust Principal Components Analysis". Test, 26(3), 461-480 <doi:10.1007/s11749-016-0519-x>.
Vardi, Y. and Zhang, C.-H. (2000). "The multivariate L1-median and associated data depth". Proc. Natl. Acad. Sci. USA, 97(4):1423-1426. <doi:10.1073/pnas.97.4.1423>.
License: GPL (>= 2)
Encoding: UTF-8
Imports: foreach, doParallel,parallel, genieclust, Gmedian,mvtnorm,
capushe, ggplot2, reshape2
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2022-09-05 11:37:54 UTC; Godichon-Baggioni
Author: Antoine Godichon-Baggioni [aut, cre, cph],
Sobihan Surendran [aut]
Maintainer: Antoine Godichon-Baggioni <antoine.godichon_baggioni@upmc.fr>
Repository: CRAN
Date/Publication: 2022-09-06 06:10:05 UTC