R/sim1.R

In topherconley/spacemap: A novel conditional graphical model for integrative genomics

#' Toy Hub Network Simulation 
#'
#'
#'  A simulation of a hub network in the high-dimension and
#'   low sample size regime. 
#'  
#'  @details The variables are as follows:
#'
#' \itemize{
#'  \item \code{Y} Numeric matrix of 150 iid samples of 171 of response variables.  
#'  \item \code{X} Numeric matrix of 150 iid samples of 14 predictor variables.  
#'  \item \code{truth} List containing
#'  \enumerate{
#'  \item \code{xy} Adjacency matrix encoding \eqn{x-y} edges. 
#'  \item \code{yy} Adjacency matrix encoding \eqn{y-y} edges. 
#'  }
#' }
#' 
#'  The simulation contains response variables \eqn{Y = (y_1, \dots, y_Q)} 
#'  and predictor variables \eqn{X = (x_1, \dots, x_P)}, where \eqn{P=14,Q=171}. 
#'  \eqn{N=150} iid samples were drawn from \eqn{(X,Y) ~ N(0, \Theta^{-1})}
#'   where non-zero off-diagonal elements of \eqn{\Theta} encode the 
#'   edges of the hub network. The network contains 
#'    10 predictors that have no edges at all, 
#'    while 2 hub predictors have 13 \eqn{x-y} edges 
#'    and 2 other hub predictors have 14 \eqn{x-y} edges.
#'    Among the response edges \eqn{y-y}, there are 2 hub variables with degree 12 and 13,
#'     but the degree of the other response variables does not exceed 4. 
#'     There are two disconnected components in the graph of size 94 and 81. 
#'     The data has been standardized (mean-centered with unit variance) for all variables. 
#' @docType data
#' @keywords datasets
#' @name sim1
#' @usage data(sim1)
#' @format A list of data elements Y,X,truth. 
NULL