On 13/09/17 11:08, Guy Bayegnak wrote:
Thanks a lot for your response and suggestion Rolf. Yes, by "quadrant" I mean
the little sub-windows. My problem is the following:
We have collected thousands of groundwater samples across a vast area, and analysed them.
Based on the analysis we are able to assign a "type" to each water sample.
When plotted, there seems to be a spatial trend in water type. But a given area may have
more than one water type, usually with a dominant type (most frequently occurring). What
I am trying to do is identify the dominant type for each sub-region /sub-windows but show
the count side by side, for example:
x
y [0,0.801) [0.801,1.6]
[0.5,1] Off = 36 Off = 6
On = 3 On = 39
[0,0.5) Off = 4 Off = 36
On = 42 On = 6
I don't understand the counts in the foregoing. Have some digits been
left off in places? I.e. should this be:
>
> x
> y [0,0.801) [0.801,1.6]
> [0.5,1] Off = 36 Off = 36
> On = 35 On = 39
>
> [0,0.5) Off = 34 Off = 36
> On = 42 On = 36 ???
>
I think I can achieve what I am looking for with your suggestion. Once I get
the table list, I will copy the numbers side by side manually.
Yeucch! Manually? Saints preserve us!
Do you really mean "quadrant" or do you simply mean *quadrat*???
Sticking with quad*rant* (it doesn't really matter), how about something
like:
rants <- tiles(quadrats(Window(amacrine),nx=2))
lapply(rants,function(w,pat){table(marks(pat[w]))},pat=amacrine)
which gives:
$`Tile row 1, col 1`
off on
36 35
$`Tile row 1, col 2`
off on
36 39
$`Tile row 2, col 1`
off on
34 42
$`Tile row 2, col 2`
off on
36 36
cheers,
Rolf
P. S. But you are probably well-advised to forget all this quadrat
counting stuff and use relrisk() as suggested by Ege Rubak.
R.
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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