如果我在R中键入example(hist)
,
我得到以下输出:
hist> op <- par(mfrow = c(2, 2))
hist> hist(islands)
Hit <Return> to see next plot:
输出中的第一行甚至不包含&#34; hist&#34;。那么如何使用&#34; hist&#34;? 也许我不理解这一点,但我想看到的只是&#34; hist&#34;用法。 请帮我解释输出。
答案 0 :(得分:8)
example(hist)
生成这三张图片:
以下文字:
hist> op <- par(mfrow=c(2, 2))
hist> hist(islands)
Waiting to confirm page change...
hist> utils::str(hist(islands, col="gray", labels = TRUE))
List of 7
$ breaks : num [1:10] 0 2000 4000 6000 8000 10000 12000 14000 16000 18000
$ counts : int [1:9] 41 2 1 1 1 1 0 0 1
$ intensities: num [1:9] 4.27e-04 2.08e-05 1.04e-05 1.04e-05 1.04e-05 ...
$ density : num [1:9] 4.27e-04 2.08e-05 1.04e-05 1.04e-05 1.04e-05 ...
$ mids : num [1:9] 1000 3000 5000 7000 9000 11000 13000 15000 17000
$ xname : chr "islands"
$ equidist : logi TRUE
- attr(*, "class")= chr "histogram"
hist> hist(sqrt(islands), breaks = 12, col="lightblue", border="pink")
hist> ##-- For non-equidistant breaks, counts should NOT be graphed unscaled:
hist> r <- hist(sqrt(islands), breaks = c(4*0:5, 10*3:5, 70, 100, 140),
hist+ col='blue1')
hist> text(r$mids, r$density, r$counts, adj=c(.5, -.5), col='blue3')
hist> sapply(r[2:3], sum)
counts intensities
48.000000 0.215625
hist> sum(r$density * diff(r$breaks)) # == 1
[1] 1
hist> lines(r, lty = 3, border = "purple") # -> lines.histogram(*)
hist> par(op)
hist> require(utils) # for str
hist> str(hist(islands, breaks=12, plot= FALSE)) #-> 10 (~= 12) breaks
List of 7
$ breaks : num [1:10] 0 2000 4000 6000 8000 10000 12000 14000 16000 18000
$ counts : int [1:9] 41 2 1 1 1 1 0 0 1
$ intensities: num [1:9] 4.27e-04 2.08e-05 1.04e-05 1.04e-05 1.04e-05 ...
$ density : num [1:9] 4.27e-04 2.08e-05 1.04e-05 1.04e-05 1.04e-05 ...
$ mids : num [1:9] 1000 3000 5000 7000 9000 11000 13000 15000 17000
$ xname : chr "islands"
$ equidist : logi TRUE
- attr(*, "class")= chr "histogram"
hist> str(hist(islands, breaks=c(12,20,36,80,200,1000,17000), plot = FALSE))
List of 7
$ breaks : num [1:7] 12 20 36 80 200 1000 17000
$ counts : int [1:6] 12 11 8 6 4 7
$ intensities: num [1:6] 0.03125 0.014323 0.003788 0.001042 0.000104 ...
$ density : num [1:6] 0.03125 0.014323 0.003788 0.001042 0.000104 ...
$ mids : num [1:6] 16 28 58 140 600 9000
$ xname : chr "islands"
$ equidist : logi FALSE
- attr(*, "class")= chr "histogram"
hist> hist(islands, breaks=c(12,20,36,80,200,1000,17000), freq = TRUE,
hist+ main = "WRONG histogram") # and warning
Waiting to confirm page change...
hist> require(stats)
hist> set.seed(14)
hist> x <- rchisq(100, df = 4)
hist> ## Don't show:
hist> op <- par(mfrow = 2:1, mgp = c(1.5, 0.6, 0), mar = .1 + c(3,3:1))
hist> ## End Don't show
hist> ## Comparing data with a model distribution should be done with qqplot()!
hist> qqplot(x, qchisq(ppoints(x), df = 4)); abline(0,1, col = 2, lty = 2)
Waiting to confirm page change...
hist> ## if you really insist on using hist() ... :
hist> hist(x, freq = FALSE, ylim = c(0, 0.2))
hist> curve(dchisq(x, df = 4), col = 2, lty = 2, lwd = 2, add = TRUE)
hist> ## Don't show:
hist> par(op)
hist> ## End Don't show
hist>
hist>
hist>
如果你没有点击Enter
/ Return
,你就会得到你发布的内容,这不是完整的例子。点击Enter
/ Return
会使图表前进,这样您就可以按顺序查看每张图片,而不是一次性查看。