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library(MASS)
#make this example reproducible
set.seed(0)
#simulate bivariate normal distribution
bivariate_data2 <- as.data.frame(mvrnorm(n=100,
mu=c(0, 0),
Sigma=matrix(c(5, 3, 4, 4), ncol=2)))
#view first six rows of bivariate dataset
head(bivariate_data2)
## V1 V2
## 1 -2.03600343 -2.9623059
## 2 0.07719131 1.2948982
## 3 -3.26729701 -1.7928069
## 4 -2.62985132 -2.3015471
## 5 -1.75126215 0.3056698
## 6 3.67698436 2.2020238
print (bivariate_data2)
## V1 V2
## 1 -2.036003431 -2.96230585
## 2 0.077191314 1.29489820
## 3 -3.267297006 -1.79280690
## 4 -2.629851319 -2.30154711
## 5 -1.751262148 0.30566984
## 6 3.676984357 2.20202377
## 7 0.945879603 2.82849217
## 8 1.886451838 -0.97474650
## 9 -0.378783529 0.47164110
## 10 -3.728486253 -5.81496521
## 11 -1.922046101 -0.97526740
## 12 0.915208484 2.31426518
## 13 2.424584695 2.01375454
## 14 0.627978563 0.48848879
## 15 -0.684664350 2.07945024
## 16 1.684877459 -0.24060586
## 17 -1.402515274 0.58402926
## 18 2.130906500 1.27392276
## 19 -0.526657622 -1.22932480
## 20 2.700875299 2.06947030
## 21 0.377190106 0.50755585
## 22 -0.636462810 -0.85206598
## 23 -1.113662486 0.74814799
## 24 -2.312104022 -0.68729390
## 25 -0.749798775 1.12772890
## 26 0.178249174 -2.35002090
## 27 -1.105822343 -3.30756840
## 28 1.652839787 0.98444157
## 29 1.729252779 3.41637306
## 30 -0.100815533 -0.07950984
## 31 1.673977453 -0.97465250
## 32 0.766200416 1.40201987
## 33 1.530838823 0.03384690
## 34 0.600532039 2.05040995
## 35 -0.984656383 -1.92529066
## 36 -3.159858979 -1.16386886
## 37 -3.040476048 -0.62608356
## 38 0.152994263 1.64420523
## 39 -3.273703534 -1.39652227
## 40 -0.125586576 1.33506727
## 41 -3.104786786 -3.80346528
## 42 -1.121488858 -1.05848588
## 43 0.696015897 1.10205716
## 44 0.895264455 2.47815520
## 45 1.651317397 3.00692114
## 46 1.633435777 2.59901102
## 47 2.402599342 3.80763638
## 48 -2.773242913 -1.63990441
## 49 -1.375188995 -1.91163955
## 50 -0.445209531 1.49137006
## 51 0.590096446 -1.82728400
## 52 -0.234425416 1.87717112
## 53 -5.190921737 -4.24458762
## 54 3.516449810 -0.77199000
## 55 0.810254756 -0.72332385
## 56 -0.721005731 -0.21161976
## 57 -1.971307291 -0.29958872
## 58 0.816505366 -0.23045229
## 59 4.650119759 3.95907427
## 60 2.355113865 2.58841308
## 61 -0.503513939 -0.92970020
## 62 -0.358440851 0.47005253
## 63 4.046487596 -0.78032130
## 64 1.554403455 -1.34282182
## 65 2.316244366 0.72820237
## 66 0.049157567 -1.08729763
## 67 2.562312997 3.02989597
## 68 -0.075301867 -1.46582912
## 69 -0.792646998 -0.11970572
## 70 -0.923739112 0.81305721
## 71 1.429963315 -1.76940203
## 72 -1.264419529 0.39928166
## 73 1.130254309 1.42313277
## 74 -0.230356818 0.77822183
## 75 -2.130945101 -0.30611890
## 76 -1.839352136 -2.50624240
## 77 -1.490662139 1.14884700
## 78 0.085776642 0.39902639
## 79 1.462800811 2.14819169
## 80 1.927048868 3.83285540
## 81 1.615228731 1.47976294
## 82 -2.964137323 -1.82899086
## 83 -2.080245636 -0.82483881
## 84 1.225873721 -0.51447179
## 85 1.305760450 0.26343017
## 86 0.807305210 0.82706701
## 87 -1.966895408 -1.91390863
## 88 0.002276799 1.16896971
## 89 -2.789004675 -2.04395199
## 90 -0.494611912 -2.16356018
## 91 -2.735618521 -2.29090687
## 92 1.956109932 1.40098939
## 93 1.563086094 -1.88072573
## 94 1.296417230 2.21206035
## 95 -0.499344228 -1.94378151
## 96 1.146885850 -1.86248001
## 97 -0.239479095 1.48152607
## 98 -3.037070965 -2.60070078
## 99 -0.784262964 -0.04721032
## 100 -2.471299038 -1.31659829
library(mnormt)
#make this example reproducible
set.seed(0)
#create bivariate normal distribution
x <- seq(-3, 3, 0.1)
y <- seq(-3, 3, 0.1)
mu <- c(0, 0)
sigma <- matrix(c(2, -1, -1, 2), nrow=2)
f <- function(x, y) dmnorm(cbind(x, y), mu, sigma)
z <- outer(x, y, f)
#create contour plot
contour(x, y, z)
library(mnormt)
#make this example reproducible
set.seed(0)
#create bivariate normal distribution
x <- seq(-3, 3, 0.1)
y <- seq(-3, 3, 0.1)
mu <- c(0, 0)
sigma <- matrix(c(2, -1, -1, 2), nrow=2)
f <- function(x, y) dmnorm(cbind(x, y), mu, sigma)
z <- outer(x, y, f)
#create surface plot
persp(x, y, z, theta=-30, phi=25, expand=0.6, ticktype='detailed')
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