Package: hopach
Version: 2.9.1
Title: Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)
Author: Katherine S. Pollard, with Mark J. van der Laan
<laan@stat.berkeley.edu> and Greg Wall
Maintainer: Katherine S. Pollard <katherine.pollard@gladstone.ucsf.edu>
Depends: R (>= 2.11.0), cluster, Biobase, methods
Imports: Biobase, cluster, graphics, grDevices, methods, stats, utils
Description: The HOPACH clustering algorithm builds a hierarchical tree
of clusters by recursively partitioning a data set, while
ordering and possibly collapsing clusters at each level. The
algorithm uses the Mean/Median Split Silhouette (MSS) criteria
to identify the level of the tree with maximally homogeneous
clusters. It also runs the tree down to produce a final ordered
list of the elements. The non-parametric bootstrap allows one
to estimate the probability that each element belongs to each
cluster (fuzzy clustering).
License: GPL (>= 2)
URL: http://www.stat.berkeley.edu/~laan/, http://docpollard.com/
biocViews: Clustering
Packaged: 2010-04-27 08:15:57 UTC; biocbuild
Repository: CRAN
Date/Publication: 2010-05-01 17:45:56

Title: Transmissions and Receptions in a Hop by Hop Network
Description: Computes the expectation of the number of transmissions and receptions considering a Hop-by-Hop transport model with limited number of retransmissions per packet. It provides the theoretical results shown in Palma et. al.(2015) <DOI:10.1109/APCASE.2015.59> and also estimated values based on Monte Carlo simulations.

Description: Computes the expectation of the number of transmissions and receptions considering a Hop-by-Hop transport model with limited number of retransmissions per packet. It provides the theoretical results shown in Palma et. al.(2016) <DOI:10.1109/TLA.2016.7555237> and also estimated values based on Monte Carlo simulations.

Description: Computes the expectation of the number of transmissions and receptions considering a Hop-by-Hop transport model with limited number of retransmissions per packet. It provides the theoretical results shown in Palma et. al.(2016) <DOI:10.1109/TLA.2016.7555237> and also estimated values based on Monte Carlo simulations. It is also possible to consider random data and ACK probabilities.