Description: Subset a control group to match an intervention group on a set of features using multivariate matching and propensity score calipers. Based on methods in Rosenbaum and Rubin (1985).
Packaged: 2018-12-19 18:50:55 UTC; eoinoconnell

Title: Model-Based Clustering and Classification with Mixtures of
Author: Jeffrey L. Andrews, Paul D. McNicholas, and Mathieu Chalifour
Maintainer: Jeffrey L. Andrews <jeffrey.andrews@macewan.ca>
Description: Fits a family of mixtures of multivariate t-distributions under a continuous t-distributed latent variable structure for the purpose of clustering or classification. The alternating expectation-conditional maximization algorithm is used for parameter estimation.

Maintainer: Jeffrey L. Andrews <jeff.andrews@ubc.ca>

Package: mmtsne
Type: Package
Title: Multiple Maps t-SNE
Author: Benjamin J. Radford
Maintainer: Benjamin J. Radford <benjamin.radford@gmail.com>
Version: 0.1.0
Description: An implementation of multiple maps t-distributed stochastic
neighbor embedding (t-SNE). Multiple maps t-SNE is a method for
projecting high-dimensional data into several low-dimensional maps such that
non-metric space properties are better preserved than they would be by a single
map. Multiple maps t-SNE with only one map is equivalent to standard t-SNE.
When projecting onto more than one map, multiple maps t-SNE estimates a set
of latent weights that allow each point to contribute to one or more maps
depending on similarity relationships in the original data. This
implementation is a port of the original 'Matlab' library by Laurens van der
Maaten.
See Van der Maaten and Hinton (2012) <doi:10.1007/s10994-011-5273-4>.
This material is based upon work supported by the United States Air Force
and Defense Advanced Research Project Agency (DARPA) under Contract No.
FA8750-17-C-0020.
Any opinions, findings and conclusions or recommendations expressed in this
material are those of the author(s) and do not necessarily reflect the views
of the United States Air Force and Defense Advanced Research Projects Agency.
Distribution Statement A: Approved for Public Release; Distribution Unlimited.
License: FreeBSD | file LICENSE
LazyData: TRUE
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-27 21:41:32 UTC; Ben
Repository: CRAN
Date/Publication: 2017-07-28 09:09:42 UTC