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信頼区間でデータをプロットするにはどうすればよいですか？

10個の値があり、それぞれに適合値Fがあり、上下の信頼区間UおよびLがある場合：

set.seed(0815)
F <- runif(10, 1, 2) 
L <- runif(10, 0, 1)
U <- runif(10, 2, 3)

これら10個の近似値とそれらの信頼区間を、以下のRのような同じプロットで表示するにはどうすればよいですか

enter image description here

rplotintervals
32
Kazo

以下がplotrixソリューションです。

set.seed(0815)
x <- 1:10
F <- runif(10,1,2) 
L <- runif(10,0,1)
U <- runif(10,2,3)

require(plotrix)
plotCI(x, F, ui=U, li=L)

enter image description here

そして、これがggplotソリューションです：

set.seed(0815)
df <- data.frame(x =1:10,
                 F =runif(10,1,2),
                 L =runif(10,0,1),
                 U =runif(10,2,3))

require(ggplot2)
ggplot(df, aes(x = x, y = F)) +
  geom_point(size = 4) +
  geom_errorbar(aes(ymax = U, ymin = L))

enter image description here

PDATE：編集の基本ソリューションは次のとおりです。

set.seed(1234)
x <- rnorm(20)
df <- data.frame(x = x,
                 y = x + rnorm(20))

plot(y ~ x, data = df)

# model
mod <- lm(y ~ x, data = df)

# predicts + interval
newx <- seq(min(df$x), max(df$x), length.out=100)
preds <- predict(mod, newdata = data.frame(x=newx), 
                 interval = 'confidence')

# plot
plot(y ~ x, data = df, type = 'n')
# add fill
polygon(c(rev(newx), newx), c(rev(preds[ ,3]), preds[ ,2]), col = 'grey80', border = NA)
# model
abline(mod)
# intervals
lines(newx, preds[ ,3], lty = 'dashed', col = 'red')
lines(newx, preds[ ,2], lty = 'dashed', col = 'red')

enter image description here

47
EDi

これは、関数plot()、polygon()およびlines()を使用したソリューションです。

 set.seed(1234)
 df <- data.frame(x =1:10,
                 F =runif(10,1,2),
                 L =runif(10,0,1),
                 U =runif(10,2,3))


 plot(df$x, df$F, ylim = c(0,4), type = "l")
 #make polygon where coordinates start with lower limit and 
 # then upper limit in reverse order
 polygon(c(df$x,rev(df$x)),c(df$L,rev(df$U)),col = "grey75", border = FALSE)
 lines(df$x, df$F, lwd = 2)
 #add red lines on borders of polygon
 lines(df$x, df$U, col="red",lty=2)
 lines(df$x, df$L, col="red",lty=2)

enter image description here

次に、OPが提供するサンプルデータを別の質問で使用します。

   Lower <- c(0.418116841, 0.391011834, 0.393297710,
        0.366144073,0.569956636,0.224775521,0.599166016,0.512269587,
        0.531378573, 0.311448219, 0.392045751,0.153614913, 0.366684097,
        0.161100849,0.700274810,0.629714150, 0.661641288, 0.533404093,
        0.412427559, 0.432905333, 0.525306427,0.224292061,
        0.28893064,0.099543648, 0.342995605,0.086973739,0.289030388,
        0.081230826,0.164505624, -0.031290586,0.148383474,0.070517523,0.009686605,
        -0.052703529,0.475924192,0.253382210, 0.354011010,0.130295355,0.102253218,
        0.446598823,0.548330752,0.393985810,0.481691632,0.111811248,0.339626541,
        0.267831909,0.133460254,0.347996621,0.412472322,0.133671128,0.178969601,0.484070587,
        0.335833224,0.037258467, 0.141312363,0.361392799,0.129791998,
        0.283759439,0.333893418,0.569533076,0.385258093,0.356201955,0.481816148,
        0.531282473,0.273126565,0.267815691,0.138127486,0.008865700,0.018118398,0.080143484,
        0.117861634,0.073697418,0.230002398,0.105855042,0.262367348,0.217799352,0.289108011,
        0.161271889,0.219663224,0.306117717,0.538088622,0.320711912,0.264395149,0.396061543,
        0.397350946,0.151726970,0.048650180,0.131914718,0.076629840,0.425849394,
        0.068692279,0.155144797,0.137939059,0.301912657,-0.071415593,-0.030141781,0.119450922,
        0.312927614,0.231345972)

 Upper.limit <- c(0.6446223,0.6177311, 0.6034427, 0.5726503,
      0.7644718, 0.4585430, 0.8205418, 0.7154043,0.7370033,
      0.5285199, 0.5973728, 0.3764209, 0.5818298,
      0.3960867,0.8972357, 0.8370151, 0.8359921, 0.7449118,
      0.6152879, 0.6200704, 0.7041068, 0.4541011, 0.5222653,
      0.3472364, 0.5956551, 0.3068065, 0.5112895, 0.3081448,
      0.3745473, 0.1931089, 0.3890704, 0.3031025, 0.2472591,
      0.1976092, 0.6906118, 0.4736644, 0.5770463, 0.3528607,
      0.3307651, 0.6681629, 0.7476231, 0.5959025, 0.7128883,
      0.3451623, 0.5609742, 0.4739216, 0.3694883, 0.5609220,
      0.6343219, 0.3647751, 0.4247147, 0.6996334, 0.5562876,
      0.2586490, 0.3750040, 0.5922248, 0.3626322, 0.5243285,
      0.5548211, 0.7409648, 0.5820070, 0.5530232, 0.6863703,
      0.7206998, 0.4952387, 0.4993264, 0.3527727, 0.2203694,
      0.2583149, 0.3035342, 0.3462009, 0.3003602, 0.4506054,
      0.3359478, 0.4834151, 0.4391330, 0.5273411, 0.3947622,
      0.4133769, 0.5288060, 0.7492071, 0.5381701, 0.4825456,
      0.6121942, 0.6192227, 0.3784870, 0.2574025, 0.3704140,
      0.2945623, 0.6532694, 0.2697202, 0.3652230, 0.3696383,
      0.5268808, 0.1545602, 0.2221450, 0.3553377, 0.5204076,
      0.3550094)

  Fitted.values<- c(0.53136955, 0.50437146, 0.49837019,
  0.46939721, 0.66721423, 0.34165926, 0.70985388, 0.61383696,
  0.63419092, 0.41998407, 0.49470927, 0.26501789, 0.47425695,
  0.27859380, 0.79875525, 0.73336461, 0.74881668, 0.63915795,
  0.51385774, 0.52648789, 0.61470661, 0.33919656, 0.40559797,
  0.22339000, 0.46932536, 0.19689011, 0.40015996, 0.19468781,
  0.26952645, 0.08090917, 0.26872696, 0.18680999, 0.12847285,
  0.07245286, 0.58326799, 0.36352329, 0.46552867, 0.24157804,
  0.21650915, 0.55738088, 0.64797691, 0.49494416, 0.59728999,
  0.22848680, 0.45030036, 0.37087676, 0.25147426, 0.45445930,
  0.52339711, 0.24922310, 0.30184215, 0.59185198, 0.44606040,
  0.14795374, 0.25815819, 0.47680880, 0.24621212, 0.40404398,
  0.44435727, 0.65524894, 0.48363255, 0.45461258, 0.58409323,
  0.62599114, 0.38418264, 0.38357103, 0.24545011, 0.11461756,
  0.13821664, 0.19183886, 0.23203127, 0.18702881, 0.34030391,
  0.22090140, 0.37289121, 0.32846615, 0.40822456, 0.27801706,
  0.31652008, 0.41746184, 0.64364785, 0.42944100, 0.37347037,
  0.50412786, 0.50828681, 0.26510696, 0.15302635, 0.25116438,
  0.18559609, 0.53955941, 0.16920626, 0.26018389, 0.25378867,
  0.41439675, 0.04157232, 0.09600163, 0.23739430, 0.41666762,
  0.29317767)

データフレームにアセンブルします（xは提供されないため、インデックスを使用します）

 df2 <- data.frame(x=seq(length(Fitted.values)),
                    fit=Fitted.values,lwr=Lower,upr=Upper.limit)
 plot(fit~x,data=df2,ylim=range(c(df2$lwr,df2$upr)))
 #make polygon where coordinates start with lower limit and then upper limit in reverse order
 with(df2,polygon(c(x,rev(x)),c(lwr,rev(upr)),col = "grey75", border = FALSE))
 matlines(df2[,1],df2[,-1],
          lwd=c(2,1,1),
          lty=1,
          col=c("black","red","red"))

enter image description here

24
Didzis Elferts

信頼区間のプロットに関連する私のプログラムの一部を次に示します。

1.テストデータを生成する

ads = 1
require(stats); require(graphics)
library(splines)
x_raw <- seq(1,10,0.1)
y <- cos(x_raw)+rnorm(len_data,0,0.1)
y[30] <- 1.4 # outlier point
len_data = length(x_raw)
N <- len_data
summary(fm1 <- lm(y~bs(x_raw, df=5), model = TRUE, x =T, y = T))
ht <-seq(1,10,length.out = len_data)
plot(x = x_raw, y = y,type = 'p')
y_e <- predict(fm1, data.frame(height = ht))
lines(x= ht, y = y_e)

結果

enter image description here

2. Bスプラインスムーザー法を使用した生データのあてはめ

sigma_e <- sqrt(sum((y-y_e)^2)/N)
print(sigma_e)
H<-fm1$x
A <-solve(t(H) %*% H)
y_e_minus <- rep(0,N)
y_e_plus <- rep(0,N)
y_e_minus[N]
for (i in 1:N)
{
    tmp <-t(matrix(H[i,])) %*% A %*% matrix(H[i,])
    tmp <- 1.96*sqrt(tmp)
    y_e_minus[i] <- y_e[i] - tmp
    y_e_plus[i] <- y_e[i] + tmp
}
plot(x = x_raw, y = y,type = 'p')
polygon(c(ht,rev(ht)),c(y_e_minus,rev(y_e_plus)),col = rgb(1, 0, 0,0.5), border = NA)
#plot(x = x_raw, y = y,type = 'p')
lines(x= ht, y = y_e_plus, lty = 'dashed', col = 'red')
lines(x= ht, y = y_e)
lines(x= ht, y = y_e_minus, lty = 'dashed', col = 'red')

結果

enter image description here

6
August