Title: Combine a Vector of Correlated p-values
Description: We offer two statistical tests to combine p-values: selfcontained.test vs competitive.test. The goal is to test whether a vector of pvalues are jointly significant when we combine them together.

Title: Estimation of Optimal Portfolio Weights by Combining Simple
Description: Estimation of optimal portfolio weights as combination of simple portfolio strategies, like the tangency, global minimum variance (GMV) or naive (1/N) portfolio. It is based on a utility maximizing 8-fund rule.

Description: Estimation of optimal portfolio weights as combination of simple portfolio strategies, like the tangency, global minimum variance (GMV) or naive (1/N) portfolio. It is based on a utility maximizing 8-fund rule. Popular special cases like the Kan-Zhou(2007) 2-fund and 3-fund rule or the Tu-Zhou(2011) estimator are nested.

Depends: R (>= 2.10), vegan, ape, picante
Maintainer: Adriano Sanches Melo <asm.adrimelo@gmail.com>
Description: Autosimilarity curves, dissimilarity indexes that overweight rare species, phylogenetic and functional (pairwise and multisample) dissimilarity indexes and nestedness for phylogenetic, functional and other diversity metrics. This should be a complement to available packages, particularly 'vegan'.

Description: Autosimilarity curves, standardization of spatial extent, dissimilarity indexes that overweight rare species, phylogenetic and functional (pairwise and multisample) dissimilarity indexes and nestedness for phylogenetic, functional and other diversity metrics. This should be a complement to available packages, particularly 'vegan'.

Depends: R (>= 2.10), vegan, ape, picante, adespatial, betapart

Title: Network-Based Communities and Kernel Machine Methods
Authors@R: c(person(given = "Alexandria", family = "Jensen",  email = "alexandria.jensen@cuanschutz.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-6337-9079")),
person(given = "Peter",      family = "DeWitt",  email = "peter.dewitt@cuanschutz.edu",      role = c("ctb"),        comment = c(ORCID = "0000-0002-6391-0795")),
person(given = "Debashis",   family = "Ghosh",   email = "debashis.ghosh@cuanschutz.edu",    role = c("ths"),        comment = c(ORCID = "0000-0001-6618-1316"))
Description: Analysis of network community objects with applications to neuroimaging data. There are two main components to this package. The first is the hierarchical multimodal spinglass (HMS) algorithm, which is a novel community detection algorithm specifically tailored to the unique issues within brain connectivity. The other is a suite of semiparametric kernel machine methods that allow for statistical inference to be performed to test for potential associations between these community structures and an outcome of interest (binary or continuous).
Imports: ggnewscale, ggplot2, gridExtra, Matrix, RColorBrewer, reshape2
Suggests: knitr, matrixcalc, pheatmap, rmarkdown
Author: Alexandria Jensen [aut, cre] (<https://orcid.org/0000-0001-6337-9079>),