将正常曲线叠加到R中的直方图

Question

我已经设法在网上找到如何将正常曲线叠加到R中的直方图，但我想保留直方图的正常“频率”y轴。请参阅下面的两个代码段，并注意在第二个代码段中，y轴被替换为“density”。如何将y轴保持为“频率”，就像在第一个图中一样。

AS A BONUS：我想在密度曲线上标记SD区域（最多3个SD）。我怎样才能做到这一点？我尝试了abline，但该行延伸到图表的顶部并且看起来很难看。

g = d$mydata
hist(g)

g = d$mydata
m<-mean(g)
std<-sqrt(var(g))
hist(g, density=20, breaks=20, prob=TRUE, 
     xlab="x-variable", ylim=c(0, 2), 
     main="normal curve over histogram")
curve(dnorm(x, mean=m, sd=std), 
      col="darkblue", lwd=2, add=TRUE, yaxt="n")

在上图中看到y轴是如何“密度”的。我想把它变成“频率”。

Answer 1

我发现这是一个很简单的方法：

h <- hist(g, breaks = 10, density = 10,
          col = "lightgray", xlab = "Accuracy", main = "Overall") 
xfit <- seq(min(g), max(g), length = 40) 
yfit <- dnorm(xfit, mean = mean(g), sd = sd(g)) 
yfit <- yfit * diff(h$mids[1:2]) * length(g) 

lines(xfit, yfit, col = "black", lwd = 2)

Answer 2

您只需要找到合适的乘数，可以从hist对象轻松计算出来。

myhist <- hist(mtcars$mpg)
multiplier <- myhist$counts / myhist$density
mydensity <- density(mtcars$mpg)
mydensity$y <- mydensity$y * multiplier[1]

plot(myhist)
lines(mydensity)

更完整的版本，密度正常，每个标准差的线条远离平均值（包括平均值）：

myhist <- hist(mtcars$mpg)
multiplier <- myhist$counts / myhist$density
mydensity <- density(mtcars$mpg)
mydensity$y <- mydensity$y * multiplier[1]

plot(myhist)
lines(mydensity)

myx <- seq(min(mtcars$mpg), max(mtcars$mpg), length.out= 100)
mymean <- mean(mtcars$mpg)
mysd <- sd(mtcars$mpg)

normal <- dnorm(x = myx, mean = mymean, sd = mysd)
lines(myx, normal * multiplier[1], col = "blue", lwd = 2)

sd_x <- seq(mymean - 3 * mysd, mymean + 3 * mysd, by = mysd)
sd_y <- dnorm(x = sd_x, mean = mymean, sd = mysd) * multiplier[1]

segments(x0 = sd_x, y0= 0, x1 = sd_x, y1 = sd_y, col = "firebrick4", lwd = 2)

Answer 3

这是上述StanLe's anwer的实现，也解决了使用密度时他的答案不会产生曲线的情况。

这将替换现有但隐藏的hist.default()函数，仅添加normalcurve参数（默认为TRUE）。

前三行用于支持roxygen2进行程序包构建。

#' @noRd
#' @exportMethod hist.default
#' @export
hist.default <- function(x,
                         breaks = "Sturges",
                         freq = NULL,
                         include.lowest = TRUE,
                         normalcurve = TRUE,
                         right = TRUE,
                         density = NULL,
                         angle = 45,
                         col = NULL,
                         border = NULL,
                         main = paste("Histogram of", xname),
                         ylim = NULL,
                         xlab = xname,
                         ylab = NULL,
                         axes = TRUE,
                         plot = TRUE,
                         labels = FALSE,
                         warn.unused = TRUE,
                         ...)  {

  # https://stackoverflow.com/a/20078645/4575331
  xname <- paste(deparse(substitute(x), 500), collapse = "\n")

  suppressWarnings(
    h <- graphics::hist.default(
      x = x,
      breaks = breaks,
      freq = freq,
      include.lowest = include.lowest,
      right = right,
      density = density,
      angle = angle,
      col = col,
      border = border,
      main = main,
      ylim = ylim,
      xlab = xlab,
      ylab = ylab,
      axes = axes,
      plot = plot,
      labels = labels,
      warn.unused = warn.unused,
      ...
    )
  )

  if (normalcurve == TRUE & plot == TRUE) {
    x <- x[!is.na(x)]
    xfit <- seq(min(x), max(x), length = 40)
    yfit <- dnorm(xfit, mean = mean(x), sd = sd(x))
    if (isTRUE(freq) | (is.null(freq) & is.null(density))) {
      yfit <- yfit * diff(h$mids[1:2]) * length(x)
    }
    lines(xfit, yfit, col = "black", lwd = 2)
  }

  if (plot == TRUE) {
    invisible(h)
  } else {
    h
  }
}

简单示例：

hist(g)

对于日期，则有所不同。供参考：

#' @noRd
#' @exportMethod hist.Date
#' @export
hist.Date <- function(x,
                      breaks = "months",
                      format = "%b",
                      normalcurve = TRUE,
                      xlab = xname,
                      plot = TRUE,
                      freq = NULL,
                      density = NULL,
                      start.on.monday = TRUE,
                      right = TRUE,
                      ...)  {

  # https://stackoverflow.com/a/20078645/4575331
  xname <- paste(deparse(substitute(x), 500), collapse = "\n")

  suppressWarnings(
    h <- graphics:::hist.Date(
      x = x,
      breaks = breaks,
      format = format,
      freq = freq,
      density = density,
      start.on.monday = start.on.monday,
      right = right,
      xlab = xlab,
      plot = plot,
      ...
    )
  )

  if (normalcurve == TRUE & plot == TRUE) {
    x <- x[!is.na(x)]
    xfit <- seq(min(x), max(x), length = 40)
    yfit <- dnorm(xfit, mean = mean(x), sd = sd(x))
    if (isTRUE(freq) | (is.null(freq) & is.null(density))) {
      yfit <- as.double(yfit) * diff(h$mids[1:2]) * length(x)
    }
    lines(xfit, yfit, col = "black", lwd = 2)
  }

  if (plot == TRUE) {
    invisible(h)
  } else {
    h
  }
}

Answer 4

去掉prob = T，让它保持默认即F