fssemR | R Documentation |
An optimizer of Fused-Sparse Structural Equation Models, which is the state of the art jointly fused sparse maximum likelihood function for structural equation models proposed by Xin Zhou and Xiaodong Cai (2018 <doi:10.1101/466623>)
Xin Zhou <xxz220@miami.edu>
seed = as.numeric(Sys.time()) N = 100 # sample size Ng = 5 # gene number Nk = 5 * 3 # eQTL number Ns = 1 # sparse ratio sigma2 = 0.01 # sigma2 set.seed(seed) library(fssemR) data = randomFSSEMdata(n = N, p = Ng, k = Nk, sparse = Ns, df = 0.3, sigma2 = sigma2, u = 5, type = "DG", nhub = 1, dag = TRUE) gamma = cv.multiRegression(data$Data$X, data$Data$Y, data$Data$Sk, ngamma = 20, nfold = 5, N, Ng, Nk) fit = multiRegression(data$Data$X, data$Data$Y, data$Data$Sk, gamma, N, Ng, Nk, trans = FALSE) Xs = data$Data$X Ys = data$Data$Y Sk = data$Data$Sk ## cross-validation ## cvfitc <- cv.multiFSSEMiPALM(Xs = Xs, Ys = Ys, Bs = fit$Bs, Fs = fit$Fs, Sk = Sk, ## sigma2 = fit$sigma2, nlambda = 10, nrho = 10, ## nfold = 5, p = Ng, q = Nk, wt = TRUE) fitm <- opt.multiFSSEMiPALM(Xs = Xs, Ys = Ys, Bs = fit$Bs, Fs = fit$Fs, Sk = Sk, sigma2 = fit$sigma2, nlambda = 10, nrho = 10, p = Ng, q = Nk, wt = TRUE) fitc0 <- fitm$fit (TPR(fitc0$Bs[[1]], data$Vars$B[[1]]) + TPR(fitc0$Bs[[2]], data$Vars$B[[2]])) / 2 (FDR(fitc0$Bs[[1]], data$Vars$B[[1]]) + FDR(fitc0$Bs[[2]], data$Vars$B[[2]])) / 2 TPR(fitc0$Bs[[1]] - fitc0$Bs[[2]], data$Vars$B[[1]] - data$Vars$B[[2]]) FDR(fitc0$Bs[[1]] - fitc0$Bs[[2]], data$Vars$B[[1]] - data$Vars$B[[2]])
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