Shingles with lattice package's equal.count()

Question

Why does the equal.count() function create overlapping shingles when it is clearly possible to create groupings with no overlap. Also, on what basis are the overlaps decided?

For example:

equal.count(1:100,4)

Data:
  [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18  19  20  21  22
 [23]  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44
 [45]  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60  61  62  63  64  65  66
 [67]  67  68  69  70  71  72  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88
 [89]  89  90  91  92  93  94  95  96  97  98  99 100

Intervals:
   min   max count
1  0.5  40.5    40
2 20.5  60.5    40
3 40.5  80.5    40
4 60.5 100.5    40

Overlap between adjacent intervals:
[1] 20 20 20

Wouldn't it be better to create groups of size 25 ? Or maybe I'm missing something that makes this functionality useful?

Answer 1

The overlap smooths transitions between the shingles (which, as the name says, overlap on the roof), but a better choice would have been to use some windowing function such as in spectral analysis.

I believe it is a pre-historic relic, because the behavior goes back to some very old pre-lattice code and is used in coplot remembered only by veteRans. lattice::equal.count calls co.intervals in graphics, where you will find some explanation. Try:

lattice:::equal.count(1:100,4,overlap=0)