Initial commit

R/deleted_funcs.R

-#'
-#' @examples
-#' 
-#' C <- matrix(rnorm(25), 5, 5)
-#' diag(C) <- rep(1, 5)
-#' C[lower.tri(C)] <- t(C)[lower.tri(C)]
-#' C2 <- pruneCorMatrix(C, 0.7)
-#' 
-
-################################################################################
-
-#' Calculate the mean and the variance of the exposure
-#'
-#' @param df is the dataframe with the cohort information
-#' @param pheno is the studied outcome
-#' @param expo is the studied exposure
-#'
-#' @return A vector of length 2 which first element is the mean and 
-#'   second element is the variance
-#'
-#' @examples
-#' # Case where E is quantitative
-#' datafr <- data.frame(floor(rnorm(5, 5000, 2000)), runif(5, 2.5, 3), runif(5, 1.2, 1.4))
-#' colnames(datafr) <- c("pheno_N", "pheno_expo_Mean", "pheno_expo_SD")
-#' params <- calculateExpoParams(df = datafr, pheno = "pheno", expo = "expo")
-#' # Case where E is binary
-#' datafr <- data.frame(floor(rnorm(5, 5000, 2000)), floor(runif(5, 1000, 3000)))
-#' colnames(datafr) <- c("pheno_N", "pheno_expo_P")
-#' params <- calculateExpoParams(df = datafr, pheno = "pheno", expo = "expo")
-#'
-#' @export
-#' 
-calculateExpoParams <- function(df, pheno, expo) {
-    if (any(grepl(paste0(pheno, "_", expo, "_P"), colnames(df)))) {
-        n <- df[, grepl("_N", colnames(df))]
-        nexp <- df[, grepl(paste0(expo, "_P"), colnames(df))]
-        meanval <- sum(nexp) / sum(n)
-        return(c(meanval, meanval * (1 - meanval)))
-    }
-    else if (any(grepl(paste0(pheno, "_", expo, "_Mean"), colnames(df))) &
-             any(grepl(paste0(pheno, "_", expo, "_SD"), colnames(df)))) {
-        n <- df[, grepl("_N", colnames(df))]
-        m <- df[, grepl(paste0(expo, "_Mean"), colnames(df))]
-        v <- df[, grepl(paste0(expo, "_SD"), colnames(df))]
-        return(calculateContParams(n, m, v))
-    }
-    else {
-        stop("Cannot calcuate exposure parameters.\nCheck columns names.")
-    }
-}
-
-################################################################################
-
-#' Perform singular Value Decomposition on the correlation matrix
-#'
-#' @param cormat is the correlation matrix
-#' @param k is the number of eigenvectors to keep. 
-#'   Default is the correlation matrix rank.
-#'
-#' @return A list with 
-#' \describe{
-#'   \item{eigval}{A vector of the top \code{k} eigenvalues}
-#'   \item{eigvev}{A matrix of the top \code{k} eigenvectors}
-#' }
-#' 
-getMatCorSVD <- function(cormat, k = qr(cormat)$rank) {
-    cormat.svd <- svd(cormat, nu = 0, nv = k)
-    list(eigval = cormat.svd$d[1:k], eigvec = cormat.svd$v)
-}
-
-################################################################################
\ No newline at end of file