基础R中的ggbiplot和biplot产生两个不同的biplots

Question

基地ggbiplot中的

biplot和R正在产生两个不同的双点。我在这里错过了什么吗？在此先感谢您的帮助。

代码

library(ggbiplot)
p <- ggbiplot(
    prcomp(dat, scale. = FALSE)
  , obs.scale = 1
  , var.scale = 1
  , labels =  rownames(dat)
  , pc.biplot = FALSE
  )
print(p)

biplot(prcomp(dat, scale. = FALSE))

输出

数据

dat <-
structure(c(-123.88909334375, 403.48715665625, 181.66403165625,
330.58653165625, 79.3502816562503, -297.19034334375, 147.59653165625,
-526.13492646875, -448.60534334375, 147.69590665625, -95.4691014687497,
91.1134066562503, 275.77986478125, 508.57653165625, -713.09159334375,
-37.6997183437503, 251.50528165625, 223.24653165625, -59.6047183437501,
-338.917218343751, 639.43132290625, 962.63257290625, 132.50944790625,
-676.94305209375, 280.14569790625, 1028.65507290625, -26.5580520937498,
-471.13951021875, -122.75992709375, 202.71632290625, 22.0179897812498,
-812.21617709375, 289.15028103125, 355.27194790625, 362.77882290625,
-482.70430209375, -380.99930209375, -1200.95805209375, -337.95930209375,
236.92819790625, 915.44132290625, 74.8425729062499, -345.73055209375,
-225.98305209375, 365.73069790625, -769.58492709375, -88.9230520937501,
-158.92951021875, 1054.47507290625, 914.07632290625, -926.64701021875,
139.61882290625, -1081.18971896875, -1465.49305209375, -762.96117709375,
152.85569790625, 569.13569790625, 734.22694790625, 657.60069790625,
247.43819790625, -331.18117709375, -408.00492709375, -150.62805209375,
164.91944790625, 17.8581979062501, 516.36757290625, 2.82944790624992,
183.27298978125, 10.7525729062502, -163.74617709375, 613.88048978125,
-137.00367709375, -202.31221896875, 384.60944790625, -24.5086770937498,
46.6831979062499, 2.53819790625016, -275.74555209375, -141.87180209375,
-108.70930209375, 330.48132290625, 1728.70757290625, 2173.55944790625,
-619.24305209375, -595.47930209375, -984.51992709375, 1877.01694790625,
-659.26451021875, -373.40992709375, 1027.09132290625, -353.60701021875,
-321.14117709375, -494.82471896875, 1596.32194790625, -712.84617709375,
-841.67930209375, 176.725697906251, -680.73305209375, -1151.08430209375,
-1122.07180209375, -268.68992709375, -1553.83867709375, 141.06319790625,
498.26069790625, 142.87444790625, 808.03382290625, 336.170697906251,
-1087.61076021875, 469.118822906251, -476.27992709375, -406.97826021875,
238.01257290625, -264.82096896875, 822.12569790625, 392.15757290625,
67.4994479062494, 606.70444790625, -171.57930209375, -225.20555209375,
-67.0180520937506, -216.15492709375, -605.45367709375, -118.90180209375,
-53.3543020937496, 7.90944790624999, 298.06882290625, 230.35569790625,
-160.05076021875, -207.52117709375, 105.45507290625, 437.28173978125,
-21.9774270937502, -154.78596896875, 116.33569790625, -305.33242709375,
640.90944790625, -257.43555209375, 372.65569790625, -414.37055209375,
306.36694790625, 85.4525729062497, 50.3038229062498, 516.03069790625,
477.45319790625, 80.3669479062504, -129.47367709375, -309.68680209375,
308.25673978125, 260.78632290625, -684.61242709375, 9.71423978125028,
133.85507290625, -264.82846896875, 72.1431979062498, -170.34992709375,
109.19194790625, -309.97805209375, 78.46319790625, -287.71305209375,
-25.3755520937503, -800.64242709375, 171.15882290625, 268.81069790625,
1.0581979062506, -48.8030520937502, 26.0813229062503, -418.05680209375,
547.161739781249, -250.33367709375, 533.49257290625, -633.33076021875,
11.6350729062499, 321.27653103125, -209.80180209375, -139.79492709375,
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366.30444790625, -644.75492709375, -436.82867709375, 834.44819790625,
-16.6543020937498, -260.94055209375, -338.85617709375, 536.50569790625,
182.19923978125, -337.496177093749, 203.25507290625, 147.58173978125,
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274.80944790625, -186.01055209375, 70.4556979062503, 579.30444790625,
-588.90805209375, 17.58507290625, 17.1613229062497, 316.21319790625,
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79.8625729062502, -784.09596896875, -1113.79930209375, -522.96742709375,
13.4994479062499, 316.60444790625, 79.99569790625, 425.66944790625,
413.65694790625, 510.48132290625, 648.95757290625, -1864.54055209375,
-708.66805209375, -841.85430209375, 496.90507290625, -426.35805209375,
-850.11451021875, 178.84007290625, 1601.51632290625, -1141.65701021875,
628.28382290625, -103.69971896875, -155.65305209375, 303.22882290625,
471.69569790625, -558.57430209375, 878.44194790625, 727.56569790625,
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141.13632290625, 263.32778103125, 162.74944790625, -392.21867709375,
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284.87257290625, 52.86403103125, 306.51069790625, 84.8425729062498,
197.73444790625, 28.56444790625, -145.51930209375, 238.32944790625,
84.0169479062499, 288.60882290625, -59.0399270937498, -280.86305209375,
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191.57298978125, -85.0474270937498, -447.12117709375, 101.38048978125,
267.17132290625, 181.01278103125, 330.48444790625, -57.85867709375,
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171.82173978125, 186.82632290625, -571.07242709375, 102.45423978125,
39.04507290625, 161.21153103125, 227.33319790625, 443.19007290625,
243.55694790625, -175.58805209375, -266.34680209375, -611.69805209375,
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602.89194790625, -655.42805209375, 503.81319790625, -179.83805209375,
54.9994479062498, -389.73909334375, -355.71284334375, 554.16403165625,
-1335.26346834375, -730.67471834375, -44.6903433437499, 1070.09653165625,
-1238.62660146875, -221.10534334375, -618.12909334375, 88.6975735312501,
-693.03659334375, 823.30486478125, 834.42653165625, -160.56659334375,
578.97528165625, 140.65528165625, 694.89653165625, -338.75471834375,
1341.08278165625), .Dim = c(20L, 40L), .Dimnames = list(c("1",
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13",
"14", "15", "16", "17", "18", "19", "20"), c("1", "2", "4", "6",
"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17",
"18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28",
"29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39",
"40", "41", "42")))

Answer 1

查看源代码，stats:biplot.default绘制硬编码缩放为0.8的箭头：

arrows(0, 0, y[,1L] * 0.8, y[,2L] * 0.8, col = col[2L], length=arrow.len)

而ggbiplot使用更加雄心勃勃的缩放（其中pcobj是您的prcomp结果）来绘制箭头：

d <- pcobj$sdev
u <- sweep(pcobj$x, 2, 1 / (d * nobs.factor), FUN = '*')
v <- pcobj$rotation
...

# Directions
v <- sweep(v, 2, d^var.scale, FUN='*')
df.v <- as.data.frame(v[, choices])
names(df.u) <- c('xvar', 'yvar')
names(df.v) <- names(df.u)
....

r <- sqrt(qchisq(circle.prob, df = 2)) * prod(colMeans(df.u^2))^(1/4)

# Scale directions
v.scale <- rowSums(v^2)
df.v <- r * df.v / sqrt(max(v.scale))
...
# Draw directions
g <- g +
  geom_segment(data = df.v,
               aes(x = 0, y = 0, xend = xvar, yend = yvar),
               arrow = arrow(length = unit(1/2, 'picas')), 
               color = muted('red'))
...