Title: Exploratory Regression 'Shiny' App
Maintainer: Catherine B. Hurley <catherine.hurley@mu.ie>
Description: Constructs a 'shiny' app function with interactive displays for summary and analysis of variance regression tables, and parallel coordinate plots of data and residuals.
Imports: shiny, RColorBrewer, ggplot2, car, leaps, broom, dplyr,
modelr, tidyr, purrr, combinat,stats, methods
Packaged: 2018-04-03 15:13:30 UTC; catherine

Imports: shiny, RColorBrewer, ggplot2, car, leaps, broom, dplyr, tidyr,
Packaged: 2018-07-24 10:55:44 UTC; catherine

Imports: shiny, miniUI,RColorBrewer, ggplot2, car, leaps, broom, dplyr,
Packaged: 2020-09-22 19:54:07 UTC; catherine

Author: Meng Hwee Victor Ong, Sanjay Chaudhuri
Maintainer: Meng Hwee Victor Ong<g0900757@nus.edu.sg>
Description: Implementation of the Edge Selection Algorithm

Title: ESEA: Discovering the Dysregulated Pathways based on Edge Set
Author: Junwei Han, Xinrui Shi, Chunquan Li
Description: The package can identify the dysregulated canonical pathways by investigating the changes of biological relationships of pathways in the context of gene expression data. (1) The ESEA package constructs a background set of edges by extracting pathway structure (e.g. interaction, regulation, modification, and binding etc.) from the seven public databases (KEGG; Reactome; Biocarta; NCI; SPIKE; HumanCyc; Panther) and the edge sets of pathways for each of the above databases. (2) The ESEA package can can quantify the change of correlation between genes for each edge based on gene expression data with cases and controls. (3) The ESEA package uses the weighted Kolmogorov-Smirnov statistic to calculate an edge enrichment score (EES), which reflects the degree to which a given pathway is associated the specific phenotype. (4) The ESEA package can provide the visualization of the results.
biocViews: Statistics, Pathways, edge, enrichment analysis
Packaged: 2015-01-22 12:50:32 UTC; Administrator

Title: ESG - A package for asset projection
Author: Jean-Charles Croix, Thierry Moudiki, Fr�d�ric Planchet, Wassim
Description: The package presents a "Scenarios" class containing
general parameters, risk parameters and projection results.
Risk parameters are gathered together into a ParamsScenarios
sub-object. The general process for using this package is to
set all needed parameters in a Scenarios object, use the
customPathsGeneration method to proceed to the projection, then
use xxx_PriceDistribution() methods to get asset prices.