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We simulate 50 observations from the linear model where the first seven coefficients are non-zero, (3;3;3;2;2;1;1). Both the covariates and random error are standard normal.

Usage

data(sim_data)

Format

A list with Xdata and Ydata 50 rows and 60 variables.

Examples

head(sim_data$Xdata)
#>              X1         X2          X3           X4          X5         X6
#> [1,]  0.4938688  0.6745728 -0.01599431 -0.173594764 -0.15676080 -1.4781466
#> [2,]  0.1527933  1.1101406 -0.97355123  1.417645262  0.18332011 -1.2565787
#> [3,]  0.6469137 -0.6880085  0.18403456 -1.070301579 -1.16021886 -0.4515424
#> [4,]  0.6966491  1.7547241 -2.07595628  1.374673169  0.85614296  0.5450787
#> [5,] -0.8270934  0.8706771 -0.92280113 -0.809768501 -2.39429594  0.1899420
#> [6,]  0.3335112 -1.8308588  0.52777766  0.008514338 -0.06878143  0.8163614
#>               X7          X8         X9         X10         X11         X12
#> [1,]  0.64552759  0.76399097  1.7200952  0.37321271  1.05804553  0.07409633
#> [2,] -0.72953466  1.53959510 -1.0039090  0.44494620 -0.07473426 -1.19461702
#> [3,]  1.61524840  1.96803115  1.1991238  0.83446932  0.14658944 -0.16839470
#> [4,] -0.06701346 -0.31578540 -1.6941367  1.58268300  0.56421158  0.78844984
#> [5,]  0.27843227 -0.52850079  0.4180275 -0.42003148  0.43225701  0.82697898
#> [6,] -0.60518421 -0.01252144 -0.2070842 -0.00215515 -0.01695024  0.55688218
#>             X13        X14        X15        X16        X17        X18
#> [1,] -0.7671330  0.3936248  0.2407562  0.5286542  0.7030770  1.2411240
#> [2,] -1.0297877 -1.2479098 -0.4941196  2.0994402 -1.8550785 -0.1514660
#> [3,]  0.6699009 -0.8386710  1.1856816 -0.4410516  0.4688541 -0.7367578
#> [4,] -0.6299289  0.1711086  0.8000159  0.4493642  1.0848850  0.1393370
#> [5,] -3.1209563 -1.5869946  0.8191613  1.3497690 -1.0829926 -0.2183456
#> [6,]  1.9757931  1.0904216 -1.2362446 -0.6611911 -0.5808356  2.1678370
#>             X19          X20       X21         X22        X23         X24
#> [1,]  0.5476494 -0.996027009 0.6687415 -2.00543812  0.3812450 -0.37494918
#> [2,] -1.2899492 -0.009910856 1.0844447 -1.60882025  1.1722107 -0.01523758
#> [3,]  0.2328182  0.507674223 0.1538086 -0.88630117 -0.2698574 -0.82663972
#> [4,]  0.3404630  1.206069263 0.7033567  0.88877945  1.0468763 -0.01610712
#> [5,]  0.8268588 -2.038457874 0.3405517  0.09982088 -2.3338276  1.98461422
#> [6,]  1.8879408 -0.101785490 0.5865799 -1.08232866 -0.5033693 -1.92313773
#>             X25        X26        X27        X28        X29        X30
#> [1,] -1.3447689 -0.8085280  0.8779621  0.4056690  1.4432472 -1.5785846
#> [2,]  1.0316120  0.5092188  1.6054660  0.2188235  0.1344156 -0.1936626
#> [3,]  0.3202443 -0.2159083  1.7266991  0.3769999 -0.7442294  1.6299211
#> [4,] -2.8896519 -1.0677098 -1.9782914 -1.1147379 -0.3616368  0.8389075
#> [5,]  0.7077275 -0.5157381  0.7138221 -0.4774671  0.1879979  0.4402057
#> [6,]  0.4827664 -0.1477384 -0.3989589  0.9312830  0.4450135  0.8256067
#>              X31        X32         X33        X34        X35        X36
#> [1,] -1.10138488 -0.2726546 -0.00800861 -0.1033703 -0.3408302  0.5579282
#> [2,] -0.67589743 -0.1723999 -0.05800819 -0.9041123  1.2918247  1.6711762
#> [3,]  0.38679555 -2.5915835  0.37692181  0.8285077 -0.3345175  1.1007352
#> [4,]  0.49160994  1.7643920  0.48086882 -0.5436240 -0.8563264 -0.9901235
#> [5,]  2.01162815  0.1697593 -0.24624946  0.6785558  0.8174315 -1.9483840
#> [6,] -0.09625376  0.9766018  0.44145638 -0.7248547 -1.2503635  0.4316713
#>              X37          X38         X39        X40        X41        X42
#> [1,]  0.57649073  0.618523403  1.75198775  1.5697131 -0.8896703 -1.3378558
#> [2,]  0.42508424  0.935360312  0.85517908 -0.2417061  1.7230421  1.1585053
#> [3,] -1.40868850  0.376441997 -0.07670675 -0.1404547 -1.6636837  0.9854857
#> [4,] -1.85451593  0.002162026  1.26772066  0.6020652  0.6299653 -1.6745796
#> [5,]  0.02086177 -0.128799013  0.18421120  0.7828179  0.3965772  0.4667499
#> [6,]  1.71064998  0.931488806  0.58478930 -0.0975153 -1.4223685 -0.1737635
#>             X43          X44         X45        X46        X47         X48
#> [1,] -0.1363042  0.441212763 -0.05689888 -0.6077480  1.4986589  0.45384986
#> [2,] -0.3390681  0.007773083 -0.34349633 -0.7263391  1.0563620  0.01030955
#> [3,]  1.5177378  0.305639050  1.84974060  0.2559957  0.7916524 -0.72163088
#> [4,] -1.8485834  0.198188472  1.83590225  1.5667756 -0.3770236  1.11786883
#> [5,]  0.5619295  0.295088587 -1.01928974  0.5150058  0.2553740  0.10960015
#> [6,] -0.4385091 -1.623669058  1.01623271  0.4819893 -0.1489744  1.11783085
#>             X49        X50        X51         X52        X53        X54
#> [1,]  0.5951266  0.5231754  0.2601639 -1.64394635 -0.7129862 -0.4486962
#> [2,] -0.7949337 -0.3496835  0.1688352  1.41167385 -0.5736820  0.2831755
#> [3,] -0.1169834  1.1788756  1.2910535  0.09534427  2.1109876  0.1649891
#> [4,]  0.7318473 -0.7925615 -1.5078384  1.09268634  1.0465558  1.2332883
#> [5,]  1.1142228 -0.7373309  1.1862115 -0.30638812  0.5976299 -1.6342983
#> [6,] -0.5701648 -1.0308343 -0.4374153  0.35273256 -0.2726438 -1.5970604
#>             X55        X56        X57        X58        X59        X60
#> [1,] -0.2891290  1.7309424  1.8044642  1.5783391  1.2279415  1.3210293
#> [2,] -0.3505132 -1.7126504 -1.6455981  1.5680606  0.6373971 -0.7927678
#> [3,]  0.9195651  2.0634599  0.1935423  0.5701249  0.8360154 -0.1910460
#> [4,] -0.7352571  0.3998000 -0.6168755 -0.3099408 -0.4906723 -0.2717122
#> [5,]  0.1759538  0.4042217 -0.4647188 -0.9894735 -0.3316086 -1.3043793
#> [6,]  0.7280478  0.1356307  0.1976618  1.4603834 -0.9153612 -1.9899105