Description: Numerical integration with Gram polynomials (based on <arXiv:2106.14875> [math.NA] 28 Jun 2021, by Irfan Muhammad [School of Computer Science, University of Birmingham, UK]).
person("Iago", "Giné-Vázquez", role = c("aut", "cre", "trl"),
person("Irfan", "Muhammad", role = "aut"))
Author: Iago Giné-Vázquez [aut, cre, trl]

Title: Graphical Representation and Modeling of Metagenomic Reads
Author: Deepak N. Ayyala, Shili Lin, Department of Statistics, The Ohio State University, Columbus, Ohio, USA.
Maintainer: Deepak Nag Ayyala <ayyala.1@osu.edu>
Description: Represents metagenomic samples on the Euclidean space to examine similarity amongst samples by studying clusters in the model. Given the matrix of metagenomic counts for samples, this package (1) quantifies dissimilarity between samples using Kendall's tau-distance, (2) constructs multidimensional models of different dimension, and (3) plots the models for visualization and comparison.
Imports: gWidgets, RGtk2, gWidgetsRGtk2, MASS, cluster, rgl, GUniFrac,
Packaged: 2014-08-10 16:28:54 UTC; DeepakNag

Packaged: 2014-12-16 04:18:31 UTC; DeepakNag

Authors@R: c(person("Deepak Nag", "Ayyala", role = c("aut", "cre"),
Maintainer: Deepak Nag Ayyala <deepaknagayyala@gmail.com>

Title: Network Topology of Intravariable Clusters with Intervariable
Maintainer: Matthew C. Bascom <matt@graphfactor.com>
Description: A Network Implementation of Fuzzy Sets: Build Network Objects from Multivariate Flat Files. For more information on fuzzy sets, refer to: Zadeh, L.A. (1964) <DOI:10.1016/S0019-9958(65)90241-X>.
Packaged: 2016-10-16 07:32:22 UTC; Engineering Broker

Title: Estimating Structural Invariants of Graphical Models
Author: Manbir Gulati, Junwei Lu, and Han Liu
Description: Efficient methods for constructing confidence intervals of monotone graph invariants, as well as testing for monotone graph properties. Many packages are available to estimate precision matrices, this package serves as a tool to extract structural properties from their induced graphs. By iteratively bootstrapping on only the relevant edge set, we are able to obtain the optimal interval size.