HistogramTools package usage in R

Question

I am generating two histograms based on the script below, they are not equal on the x axis and as I wish to compare them I can not do so. Therefore, what can I do to run the script properly, any ideas how to approach this issue?

Thanks

x<-c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 3, 
      2, 6, 5, 13, 12, 15, 27, 34, 37, 58, 85, 90, 111, 131, 161, 164, 
      191, 211, 267, 293, 288, 320, 364, 370, 379, 413, 429, 473, 546, 
      539, 551, 593, 614, 594, 644, 617, 599, 605, 531, 591, 524, 482, 
      470, 437, 446, 428, 384, 368, 331, 332, 320, 317, 295, 266, 286, 
      284, 342, 360, 394, 480, 502, 600, 547, 610, 524, 545, 497, 414, 
      381, 345, 351, 371, 326, 336, 341, 336, 324, 346, 360, 386, 368, 
      396, 428, 432, 434, 438, 513, 498, 452, 452, 403, 397, 407, 405, 
      460, 515, 541, 608, 522, 542, 514, 517, 551, 661, 669, 739, 805, 
      847, 921, 1031, 965, 973, 1030, 1043, 815, 818, 648, 520, 433, 
      338, 295, 162, 106, 70, 44, 15, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)

y<-c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 
      1, 1, 6, 4, 11, 4, 9, 15, 12, 34, 40, 49, 75, 65, 107, 132, 136, 
      157, 178, 189, 217, 278, 276, 296, 323, 435, 464, 473, 581, 613, 
      705, 820, 925, 1025, 1061, 1080, 1176, 1236, 1166, 1075, 1027, 
      976, 935, 807, 697, 658, 593, 440, 408, 347, 312, 296, 242, 284, 
      260, 243, 254, 283, 291, 371, 444, 470, 607, 719, 676, 722, 644, 
      678, 650, 662, 666, 607, 621, 558, 623, 634, 634, 699, 756, 771, 
      790, 852, 893, 1011, 1048, 1010, 966, 936, 860, 791, 681, 686, 
      752, 850, 952, 1049, 1094, 1134, 1156, 1198, 1351, 1342, 1533, 
      1461, 1271, 1065, 865, 739, 534, 459, 359, 275, 169, 124, 108, 
      80, 74, 64, 69, 61, 59, 56, 60, 76, 113, 102, 132, 101, 79, 92, 
      55, 41, 26, 17, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
      0, 0, 0)

h1 <- hist(x)
h2 <- hist(y)

require(HistogramTools) 

minkowski.dist(h1, h2, 1)
minkowski.dist(h1, h2, 2)
minkowski.dist(h1, h2, 3)
intersect.dist(h1, h2)
kl.divergence(h1, h2)
jeffrey.divergence(h1, h2)

Answer 1

Both vectors (x and y) have 256 observations. Are these observations paired, ie, for each x there is a corresponding y, and they have the same unit of measurement?

If yes, you can subtract one vector from the other and just plot the histogram of their differences to compare each other. Something like below:

length(x) #check number os observations in x
length(y) #check number os observations in y
diff = x-y #difference between x and y
hist(diff, xlab="x-y", main="Difference of vectors x and y") 

If the x and y cannot be paired, but they have the same unit of measument there is the option provided by Hav0k.
Set the axis on both histograms with the same length and breaks to visually compare each other.

par(mfrow=c(1,2)) #stacks hisotgrams in one row and two columns
hist(x, xlim=c(0,1600), ylim=c(0,200), breaks=seq(0,1600,100),main="") 
hist(y, xlim=c(0,1600), ylim=c(0,200), breaks=seq(0,1600,100),main="")

It is also possible to calculate the dissimilarity metrics with these:

h1 = hist(x, xlim=c(0,1600), ylim=c(0,200), breaks=seq(0,1600,100),main="") 
h2 = hist(y, xlim=c(0,1600), ylim=c(0,200), breaks=seq(0,1600,100),main="")
minkowski.dist(h1, h2, 1) #116
minkowski.dist(h1, h2, 2) #38.88
minkowski.dist(h1, h2, 3) #29.81
intersect.dist(h1, h2) #0.22

If x and y have different units of measurements there is the option of standardizing the data before computing the dissimilarities.

x_standardized = (x-mean(x))/(sd(x))
y_standardized = (y-mean(y))/(sd(y))
h1=hist(x_standardized)
h2=hist(y_standardized)
minkowski.dist(h1, h2, 1) #58
minkowski.dist(h1, h2, 2)#26.57
minkowski.dist(h1, h2, 3) #22.1
intersect.dist(h1, h2) # 0.11
kl.divergence(h1, h2) # 0.07
jeffrey.divergence(h1, h2) #0.03