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Type 'q()' to quit R. > library("matrixStats") > > set.seed(1) > x <- rnorm(1e4) > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Variance estimators > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > sigma2_a <- var(x) > cat(sprintf("var(x) = %g\n", sigma2_a)) var(x) = 1.02487 > > sigma2_b <- varDiff(x) > cat(sprintf("varDiff(x) = %g\n", sigma2_b)) varDiff(x) = 1.01224 > > d <- abs(sigma2_b - sigma2_a) > cat(sprintf("Absolute difference = %g\n", d)) Absolute difference = 0.0126268 > stopifnot(d < 0.02) > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Standard deviation estimators > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > sigma_a <- sd(x) > cat(sprintf("sd(x) = %g\n", sigma_a)) sd(x) = 1.01236 > > sigma_b <- sdDiff(x) > cat(sprintf("sdDiff(x) = %g\n", sigma_b)) sdDiff(x) = 1.0061 > > d <- abs(sigma_b - sigma_a) > cat(sprintf("Absolute difference = %g\n", d)) Absolute difference = 0.00625567 > stopifnot(d < 0.01) > > # Sanity checks > stopifnot(abs(sigma2_a - sigma_a ^ 2) < 1e-9) > stopifnot(abs(sigma2_b - sigma_b ^ 2) < 1e-9) > > > sigma_a2 <- mad(x) > cat(sprintf("mad(x) = %g\n", sigma_a2)) mad(x) = 0.998376 > > sigma_b2 <- madDiff(x) > cat(sprintf("madDiff(x) = %g\n", sigma_b2)) madDiff(x) = 1.02513 > > d <- abs(sigma_b2 - sigma_a2) > cat(sprintf("Absolute difference = %g\n", d)) Absolute difference = 0.0267497 > stopifnot(d < 0.05) > > > sigma_a3 <- IQR(x) > cat(sprintf("IQR(x) = %g\n", sigma_a3)) IQR(x) = 1.35105 > > sigma_b3 <- iqrDiff(x) > cat(sprintf("iqrDiff(x) = %g\n", sigma_b3)) iqrDiff(x) = 1.37797 > > d <- abs(sigma_b3 - sigma_a3) > cat(sprintf("Absolute difference = %g\n", d)) Absolute difference = 0.0269152 > stopifnot(d < 0.05) > > > > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > # Trimmed estimators > # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - > y <- x > outliers <- sample(length(x), size = 0.1 * length(x)) > y[outliers] <- 100 * y[outliers] > > sigma_ao <- sd(y[-outliers]) > cat(sprintf("sd(y) = %g\n", sigma_ao)) sd(y) = 1.01166 > > sigma_bo <- sdDiff(y[-outliers]) > cat(sprintf("sdDiff(y) = %g\n", sigma_bo)) sdDiff(y) = 1.00743 > > d <- abs(sigma_b - sigma_a) > cat(sprintf("Absolute difference = %g\n", d)) Absolute difference = 0.00625567 > stopifnot(d < 0.01) > > sigma_bot <- sdDiff(y, trim = 0.05) > cat(sprintf("sdDiff(y, trim = 0.05) = %g\n", sigma_bot)) sdDiff(y, trim = 0.05) = 7.74327 > > d <- abs(sigma_bot - sigma_a) > cat(sprintf("Absolute difference = %g\n", d)) Absolute difference = 6.73091 > #stopifnot(d < 1e-3) > > sigma_cot <- madDiff(y, trim = 0.05) > cat(sprintf("madDiff(y, trim = 0.05) = %g\n", sigma_cot)) madDiff(y, trim = 0.05) = 1.15278 > > sigma_dot <- iqrDiff(y, trim = 0.05) > cat(sprintf("iqrDiff(y, trim = 0.05) = %g\n", sigma_dot)) iqrDiff(y, trim = 0.05) = 1.55762 > > > fcns <- list( + varDiff = varDiff, + sdDiff = sdDiff, + madDiff = madDiff, + iqrDiff = iqrDiff + ) > > for (name in names(fcns)) { + cat(sprintf("%s()...\n", name)) + fcn <- fcns[[name]] + + for (mode in c("integer", "double")) { + cat("mode: ", mode, "", sep = "") + for (n in 0:3) { + x <- runif(n, min = -5, max = 5) + storage.mode(x) <- mode + str(x) + + y <- fcn(x) + yt <- fcn(x, trim = 0.1) + str(list("non-trimmed" = y, trimmed = yt)) + } # for (mode ...) + } + + cat(sprintf("%s()...DONE\n", name)) + } # for (name ...) varDiff()... mode: integer int(0) List of 2 $ non-trimmed: num NA $ trimmed : num NA int -4 List of 2 $ non-trimmed: num NA $ trimmed : num NA int [1:2] 3 2 List of 2 $ non-trimmed: num NA $ trimmed : num NA int [1:3] 1 4 -1 List of 2 $ non-trimmed: num 16 $ trimmed : num 16 mode: double num(0) List of 2 $ non-trimmed: num NA $ trimmed : num NA num -0.794 List of 2 $ non-trimmed: num NA $ trimmed : num NA num [1:2] 0.897 -3.728 List of 2 $ non-trimmed: num NA $ trimmed : num NA num [1:3] 2.07 -1.13 1.94 List of 2 $ non-trimmed: num 9.83 $ trimmed : num 9.83 varDiff()...DONE sdDiff()... mode: integer int(0) List of 2 $ non-trimmed: num NA $ trimmed : num NA int 2 List of 2 $ non-trimmed: num NA $ trimmed : num NA int [1:2] -4 1 List of 2 $ non-trimmed: num NA $ trimmed : num NA int [1:3] -2 1 -1 List of 2 $ non-trimmed: num 2.5 $ trimmed : num 2.5 mode: double num(0) List of 2 $ non-trimmed: num NA $ trimmed : num NA num -3.78 List of 2 $ non-trimmed: num NA $ trimmed : num NA num [1:2] -2.04 2.38 List of 2 $ non-trimmed: num NA $ trimmed : num NA num [1:3] 1.42 -2.14 1.14 List of 2 $ non-trimmed: num 3.42 $ trimmed : num 3.42 sdDiff()...DONE madDiff()... mode: integer int(0) List of 2 $ non-trimmed: num NA $ trimmed : num NA int -1 List of 2 $ non-trimmed: num NA $ trimmed : num NA int [1:2] -1 4 List of 2 $ non-trimmed: num NA $ trimmed : num NA int [1:3] -1 0 -3 List of 2 $ non-trimmed: num 2.1 $ trimmed : num 2.1 mode: double num(0) List of 2 $ non-trimmed: num NA $ trimmed : num NA num -1.13 List of 2 $ non-trimmed: num NA $ trimmed : num NA num [1:2] -1.7 -1.21 List of 2 $ non-trimmed: num NA $ trimmed : num NA num [1:3] -2.39 -0.464 3.086 List of 2 $ non-trimmed: num 0.851 $ trimmed : num 0.851 madDiff()...DONE iqrDiff()... mode: integer int(0) List of 2 $ non-trimmed: num NA $ trimmed : num NA int 3 List of 2 $ non-trimmed: num 0 $ trimmed : num 0 int [1:2] -3 4 List of 2 $ non-trimmed: num 0 $ trimmed : num 0 int [1:3] 0 -2 -2 List of 2 $ non-trimmed: num 0.707 $ trimmed : num 0.707 mode: double num(0) List of 2 $ non-trimmed: num NA $ trimmed : num NA num -4.46 List of 2 $ non-trimmed: num 0 $ trimmed : num 0 num [1:2] 3.67 1.02 List of 2 $ non-trimmed: num 0 $ trimmed : num 0 num [1:3] -0.537 -2.733 2.857 List of 2 $ non-trimmed: num 2.75 $ trimmed : num 2.75 iqrDiff()...DONE > > proc.time() user system elapsed 0.26 0.09 0.34