将95％的置信度限制添加到累积图

|| 我想在R硬币投掷图中添加一条表示95％置信范围的抛物线：

x  <- sample(c(-1,1), 60000, replace = TRUE)
plot.ts(cumsum(x), ylim=c(-250,250))

这是我要寻找的示例：更新：@ bill_080 \的答案很好。但是我已经计算了100,000次抛硬币：

str(100ktoss)
num [1:100000] -1 1 1 1 -1 -1 1 -1 -1 -1 ...

我真的只想在该图上添加95％的限制：

plot.ts(cumsum(100ktoss))

计算我的100K硬币抛掷花了几个小时，当我尝试使用@ bill_080 \的代码进行复制时，我的内存不足（100,000个）。最后更新：好的。最后一个问题。我在一张图表上有几轮累积命中的图，每轮的开始都固定在零（实际上是1或-1，取决于是赢还是输）。

>str(1.ts)  
Time-Series [1:35] from 1 to 35: 1 2 1 2 3 4 5 4 5 6 ...  
>str(2.ts)  
Time-Series [1:150] from 36 to 185: -1 0 1 0 -1 -2 -1 0 1 2 ...

我想像这样向每个细分市场添加相同的95％限制。现在解决： @ bill_080非常感谢。这是最终产品：

已邀请:

1 个回复

矾醒忻

尝试这个。所有循环均为for循环，因此您可以轻松添加更多计算。

#Set the number of bets and number of trials and % lines
numbet <- 6000 #6000 bets
numtri <- 1000 #Run 1000 trials of the 6000 bets
perlin <- 0.05 #Show the +/- 5% lines on the graph
rantri <- 60 #The 60th trial (just a random trial to be drawn)

#Fill a matrix where the rows are the cumulative bets and the columns are the trials
xcum <- matrix(NA, nrow=numbet, ncol=numtri)
for (i in 1:numtri) {
  x <- sample(c(-1,1), numbet, replace = TRUE)
  xcum[,i] <- cumsum(x)
}

#Plot the trials as transparent lines so you can see the build up
matplot(xcum, type=\"l\", xlab=\"Number of Bets\", ylab=\"Cumulative Sum\", main=\"Cumulative Results\", col=rgb(0.01, 0.01, 0.01, 0.02))
grid()

#Sort the trials of each bet so you can pick out the desired %
xcumsor <- xcum
for (i in 1:numbet) {
  xcumsor[i,] <- xcum[i,order(xcum[i,])]
}

#Draw the upper/lower limit lines and the 50% probability line     
lines(xcumsor[, perlin*numtri], type=\"l\", lwd=2, col=rgb(1, 0.0, 0.0)) #Lower limit
lines(xcumsor[, 0.5*numtri], type=\"l\", lwd=3, col=rgb(0, 1, 0.0)) #50% Line
lines(xcumsor[, (1-perlin)*numtri], type=\"l\", lwd=2, col=rgb(1, 0.0, 0.0)) #Upper limit

#Show one of the trials
lines(xcum[, rantri], type=\"l\", lwd=1, col=rgb(1, 0.8, 0)) #Random trial

#Draw the legend
legend(\"bottomleft\", legend=c(\"Various Trials\", \"Single Trial\", \"50% Probability\", \"Upper/Lower % Limts\"), bg=\"white\", lwd=c(1, 1, 3, 2), col=c(\"darkgray\", \"orange\", \"green\", \"red\"))

编辑1 =============================================== ========== 如果您只是想画出+/- 5％的线，那只是平方根函数。这是代码：

#Set the bet sequence and the % lines
betseq <- 1:100000 #1 to 100,000 bets
perlin <- 0.05 #Show the +/- 5% lines on the graph

#Calculate the Upper and Lower limits using perlin
#qnorm() gives the multiplier for the square root
upplim <- qnorm(1-perlin)*sqrt(betseq)
lowlim <- qnorm(perlin)*sqrt(betseq)

#Get the range for y
yran <- range(upplim, lowlim)

#Plot the upper and lower limit lines
plot(betseq, upplim, ylim=yran, type=\"l\", xlab=\"\", ylab=\"\")
lines(betseq, lowlim)

编辑2 =============================================== == 要在正确的位置添加抛物线，定义函数可能会更容易。请记住，由于新函数（dralim）使用lines，因此在调用dralim之前必须存在该图。使用与Edit 1中的代码相同的一些变量：

#Set the bet sequence and the % lines
betseq <- 0:700 #0 to 700 bets
perlin <- 0.05 #Show the +/- 5% lines on the graph

#Define a function that plots the upper and lower % limit lines
dralim <- function(stax, endx, perlin) {
  lines(stax:endx, qnorm(1-perlin)*sqrt((stax:endx)-stax))
  lines(stax:endx, qnorm(perlin)*sqrt((stax:endx)-stax))
}

#Build the plot area and draw the vertical dashed lines
plot(betseq, rep(0, length(betseq)), type=\"l\", ylim=c(-50, 50), main=\"\", xlab=\"Trial Number\", ylab=\"Cumulative Hits\")
abline(h=0)
abline(v=35, lty=\"dashed\") #Seg 1
abline(v=185, lty=\"dashed\") #Seg 2
abline(v=385, lty=\"dashed\") #Seg 3
abline(v=485, lty=\"dashed\") #Seg 4
abline(v=585, lty=\"dashed\") #Seg 5

#Draw the % limit lines that correspond to the vertical dashed lines by calling the
#new function dralim.
dralim(0, 35, perlin) #Seg 1
dralim(36, 185, perlin) #Seg 2
dralim(186, 385, perlin) #Seg 3
dralim(386, 485, perlin) #Seg 4
dralim(486, 585, perlin) #Seg 5
dralim(586, 701, perlin) #Seg 6

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将95％的置信度限制添加到累积图

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将95％的置信度限制添加到累积图

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