r累积图简单化及其应称为什么

Question

I have a numeric vector data . I need to gather the following data, ie, histogram, but in a cumulative sense.

a=c()
s=seq(0,1000,10)
for(i in s)
{
    a<-c(a,length(data[data>=i]))
}
plot(s,a)

How can I make this vectorized, and what should this operation be called? It is currently not very good, because I have to know the range in order to write s in the above, is there any existing function in R that does this operation?

Thank you.

Answer 1

Something like this??

set.seed(1)          # for reproducible example
data <- rnorm(100)   # random sample from N(0,1)
par(mfrow=c(1,2))    # set up graphics device for 2 plots

z <- hist(data,ylab="Counts",main="Histogram")
barplot(cumsum(z$counts), names.arg=z$breaks[-1],main="Cuml. Histogram")

This takes advantage of the fact that the hist(...) function not only plots a histogram, but returns and object of type histogram . This object has elements $breaks containing upper and lower limits on the histogram bins, and $counts containing the count of data in each bin. The cumsum function calculates the cumulative sum. So the plot on the right is just the cumulative sum of the counts vs. the breaks.

Another, slightly simpler way to do this is to "hack" the histogram object returned by hist(...) and then use plot(...) on that:

z <- hist(data,ylab="Counts",main="Histogram")
z$counts <- cumsum(z$counts)
plot(z, main="Cuml. Histogram")

Finally, ecdf(...) (empirical cumulative distribution function) returns a function that can be plotted easily.

plot(ecdf(data))

Answer 2

I would convert to factors with as many levels as you want bins, and then use table and cumsum on that.

For example:

# Create some fake data:
> tst = sample(1:50,10)
> tst
 [1] 33  7 13 19  1 18 39 15 21 25

# create a vector of factors with all possible levels from "min(tst)" until "max(tst)":
> tst2 = factor(as.character(tst),levels=paste0(min(tst):max(tst)))
> tst2
 [1] 33 7  13 19 1  18 39 15 21 25
39 Levels: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 ... 39

# finally, get in one (vectorized) operation the distribution of values >= levels (for each level):
> cumsum(table(tst2))
 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 
 1  1  1  1  1  1  2  2  2  2  2  2  3  3  4  4  4  5  6  6  7  7  7  7  8  8  8  8 
29 30 31 32 33 34 35 36 37 38 39 
 8  8  8  8  9  9  9  9  9  9 10 

Does this help?

edit:

I just realized that this gives you the number of items whose value is less than a given threshold. You can obtain what you want with:

> tst3 = rev(cumsum(table(tst2)))
> names(tst3) = rev(names(tst3))
> tst3
 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 
10  9  9  9  9  9  9  8  8  8  8  8  8  8  8  7  7  7  7  6  6  5  4  4  4  3  3  2 
29 30 31 32 33 34 35 36 37 38 39 
 2  2  2  2  2  1  1  1  1  1  1 

edit 2:

Much simpler in fact:

> sapply(min(tst):max(tst), function(x)sum(tst>=x))
 [1] 10  9  9  9  9  9  9  8  8  8  8  8  8  7  7  6  6  6  5  4  4  3  3  3  3  2
[27]  2  2  2  2  2  2  2  1  1  1  1  1  1