tests/testthat/test_alpha_estimation.R

In YipengUva/RpESCA: R implementaion of pESCA models with various concave penalties

# test alpha estimation procedure
n <- 200
ds <- c(400, 200, 100)
simulatedData <- dataSimu_group_sparse(n = n, ds = ds, 
                                       dataTypes = "GGG", 
									   noises = rep(1, 3), 
									   margProb = 0.1, 
									   sparse_ratio = 0, 
									   SNRgc = 1, 
									   SNRlc = rep(1, 3), 
									   SNRd = rep(1, 3))
dataSets <- simulatedData$X
alphas_est <- rep(NA, 3)

opts <- list()
opts$tol_obj <- 1e-04
opts$quiet <- 1

for (i in 1:3) {
    # index ith data set
    X <- dataSets[[i]]
    
    # add element-wise missing pattern
    full_indexes <- 1:(n * dim(X)[2])
    missing_index <- sample(full_indexes, round(0.1 * length(full_indexes)))
    X[missing_index] <- NA
    
    # add row-wise and column-wise missing pattern
    X[sample(1:n, round(0.1 * n)), ] <- NA
    X[, sample(1:dim(X)[2], round(0.1 * dim(X)[2]))] <- NA
    
    # alpha estimation procedure
    alpha_test <- alpha_estimation(X, K = 3, Rs = 5:20, opts = opts)
    alphas_est[i] <- alpha_test$alphas_mean
}
expect_equal(rep(1, 3), alphas_est, tolerance = 0.1)