Sure! Although I'm not sure how to use dput()
Here is more detail and some data.... what I want is that the repetitions
in Y (at the end) only have 1 or 0...
> library(reshape)
> library(car)
>
> ###Read in the occurence data
> occ.data <- read.table("Occ_short.csv",
header=TRUE,sep=",",na.strings=TRUE) #occ data from 2007-2008
> occ.data[1:30,]
Año Punto Especie Pres Ruta_com Point Site Rep
1 2012 30 TYSA 1 108 30 1086 5
2 2012 26 VACH 1 108 26 1086 1
3 2012 27 VACH 1 108 27 1086 2
4 2012 26 ZEAU 1 108 26 1086 1
5 2012 27 ZEAU 1 108 27 1086 2
6 2012 28 ZEAU 1 108 28 1086 3
7 2012 30 ZEAU 1 108 30 1086 5
8 2012 7 TYSA 1 111 7 1112 2
9 2012 6 ZEAU 1 111 6 1112 1
10 2012 10 ZEAU 1 111 10 1112 5
11 2012 24 TYSA 1 111 24 1115 4
12 2012 23 VACH 1 111 23 1115 3
13 2012 21 ZEAU 1 111 21 1115 1
14 2012 23 ZEAU 1 111 23 1115 3
15 2012 24 ZEAU 1 111 24 1115 4
16 2012 25 ZEAU 1 111 25 1115 5
17 2012 28 AMHU 1 111 28 1116 3
18 2012 29 AMHU 1 111 29 1116 4
19 2012 30 AMHU 1 111 30 1116 5
20 2012 27 TYSA 1 111 27 1116 2
21 2012 26 VACH 1 111 26 1116 1
22 2012 27 VACH 1 111 27 1116 2
23 2012 26 ZEAU 1 111 26 1116 1
24 2012 27 ZEAU 1 111 27 1116 2
25 2012 29 ZEAU 1 111 29 1116 4
26 2012 28 ZOCA 1 111 28 1116 3
27 2012 29 ZOCA 1 111 29 1116 4
28 2012 30 ZOCA 1 111 30 1116 5
29 2012 5 AMHU 1 205 5 2051 5
30 2012 3 SILU 1 205 3 2051 3
>
> ########################################
> ###### RECODE SPECIES INTO GUILDS
> #########################################
>
> occ.data$guild<- recode(occ.data$Especie,
"c('AMHU','SILU','ZOCA')='gui4b';else='OTHER'")
> occ.data[1:30,]
Año Punto Especie Pres Ruta_com Point Site Rep guild
1 2012 30 TYSA 1 108 30 1086 5 OTHER
2 2012 26 VACH 1 108 26 1086 1 OTHER
3 2012 27 VACH 1 108 27 1086 2 OTHER
4 2012 26 ZEAU 1 108 26 1086 1 OTHER
5 2012 27 ZEAU 1 108 27 1086 2 OTHER
6 2012 28 ZEAU 1 108 28 1086 3 OTHER
7 2012 30 ZEAU 1 108 30 1086 5 OTHER
8 2012 7 TYSA 1 111 7 1112 2 OTHER
9 2012 6 ZEAU 1 111 6 1112 1 OTHER
10 2012 10 ZEAU 1 111 10 1112 5 OTHER
11 2012 24 TYSA 1 111 24 1115 4 OTHER
12 2012 23 VACH 1 111 23 1115 3 OTHER
13 2012 21 ZEAU 1 111 21 1115 1 OTHER
14 2012 23 ZEAU 1 111 23 1115 3 OTHER
15 2012 24 ZEAU 1 111 24 1115 4 OTHER
16 2012 25 ZEAU 1 111 25 1115 5 OTHER
17 2012 28 AMHU 1 111 28 1116 3 gui4b
18 2012 29 AMHU 1 111 29 1116 4 gui4b
19 2012 30 AMHU 1 111 30 1116 5 gui4b
20 2012 27 TYSA 1 111 27 1116 2 OTHER
21 2012 26 VACH 1 111 26 1116 1 OTHER
22 2012 27 VACH 1 111 27 1116 2 OTHER
23 2012 26 ZEAU 1 111 26 1116 1 OTHER
24 2012 27 ZEAU 1 111 27 1116 2 OTHER
25 2012 29 ZEAU 1 111 29 1116 4 OTHER
26 2012 28 ZOCA 1 111 28 1116 3 gui4b
27 2012 29 ZOCA 1 111 29 1116 4 gui4b
28 2012 30 ZOCA 1 111 30 1116 5 gui4b
29 2012 5 AMHU 1 205 5 2051 5 gui4b
30 2012 3 SILU 1 205 3 2051 3 gui4b
>
> #############################################
> ####The detection/non-detection data is reshaped into a four dimensional
> #array "y" where the first dimension, j, is the point; the second
> #dimension, k, is the rep; the third dimension, i, is the guild; and the
last
> #dimension t, is the year
>
> junk.melt=melt(occ.data,id.var=c("guild", "Site", "Rep", "Año"),
measure.var="Pres")
> y=cast(junk.melt, Site ~ Rep ~ guild ~ Año)
Aggregation requires fun.aggregate: length used as default
> y
, , guild = gui4b, Año = 2012
Rep
Site 1 2 3 4 5
1086 0 0 0 0 0
1112 0 0 0 0 0
1115 0 0 0 0 0
1116 0 0 2 2 2
2051 1 0 1 1 3
2055 1 0 0 3 2
2056 0 1 1 0 0
, , guild = OTHER, Año = 2012
Rep
Site 1 2 3 4 5
1086 2 2 1 0 2
1112 1 1 0 0 1
1115 1 0 2 2 1
1116 2 3 0 1 0
2051 2 3 1 1 3
2055 1 2 2 1 0
2056 1 2 1 1 0
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