I'm getting an "NaN" test result using the R package adehabitatHS, and the function "compana".
The compana test compares habitat availability with habitat usage by animals. The test performs a compositional analysis (Aebischer et al. 1993), yielding a value for Wilk's lambda and a p-value.
I'm running the test on empirical data for rattlesnakes (16 animals, 8 habitat categories). For some reason the compana test returns: lambda = NaN, p-value = 1.0.
I've examined my data for the standard causes of NaNs, and I don't see any problems, such as missing values (NAs), negative proportions, or row sums > 100 percent. Moreover, the error arises when I use the full data set (16 rows, 8 columns), but not when I use a subset (missing one column). It does not seem to matter which column(s) is excluded, so long as only 7 or less are included.
Details of my data are below. Any help or suggestions would be greatly appreciated.
Platform: OSX 10.7.4 (Lion) R Version: R 2.15.1 GUI 1.52 Leopard build 64-bit (6188)
R CODE:
proportions for habitat used (matrix):
used.m
Atr Cre DW Dist Gra Mar Mes Opn
1 2.76 19.31 4.14 17.24 0.00 28.28 0.00 0.00
2 15.12 1.16 3.49 5.81 2.33 32.56 25.58 3.49
3 57.35 13.24 1.47 0.00 6.62 0.00 8.09 12.50
4 41.18 0.98 2.94 0.00 3.92 0.00 29.41 18.63
5 9.52 17.01 23.13 0.00 0.00 37.41 3.40 0.00
6 2.54 67.01 0.00 0.51 0.51 6.09 3.05 0.00
7 10.45 15.67 5.22 5.97 0.00 0.00 33.58 10.45
8 6.34 0.00 0.00 4.23 0.00 0.00 0.00 21.83
9 0.66 18.54 1.32 39.74 0.00 8.61 2.65 0.66
10 20.75 0.00 0.00 0.00 0.00 0.00 0.00 49.06
11 20.14 18.06 12.50 8.33 0.00 5.56 22.22 9.72
12 0.00 0.00 0.00 58.04 0.00 0.00 13.99 0.00
13 44.23 4.81 0.00 0.00 0.00 0.00 28.85 19.23
14 13.04 2.61 1.74 2.61 0.00 19.13 6.09 25.22
15 35.96 3.51 0.00 2.63 0.00 1.75 25.44 0.88
16 0.00 0.00 0.00 35.14 0.00 7.21 0.00 8.11
proportions for habitat available (matrix):
avail.m
Atr Cre DW Dist Gra Mar Mes Opn
1 1.11 39.18 15.50 0.29 0.00 30.18 4.15 3.43
2 18.96 1.02 0.87 7.40 4.36 37.80 6.17 10.56
3 65.75 3.85 0.57 0.00 12.36 0.00 9.97 3.43
4 20.52 5.44 2.01 0.00 0.08 0.00 10.99 44.22
5 11.16 43.55 10.34 0.00 0.00 18.11 9.60 3.17
6 25.24 9.88 2.77 2.44 4.95 12.90 11.44 2.19
7 5.47 21.13 6.67 0.57 0.00 0.10 30.73 9.59
8 6.23 0.00 0.00 4.85 0.00 0.00 0.00 5.72
9 0.85 1.97 0.09 33.52 0.00 5.58 1.73 0.84
10 18.97 0.00 0.00 0.00 0.00 0.00 0.00 5.59
11 0.16 44.41 19.16 3.53 0.00 1.28 21.65 4.13
12 6.67 3.89 0.31 13.63 0.00 0.00 20.56 0.00
13 21.40 2.38 2.66 0.00 0.00 0.00 21.23 46.96
14 42.62 9.36 1.49 3.89 0.43 3.61 20.79 5.80
15 33.32 12.90 4.17 4.09 0.15 3.96 12.32 4.94
16 5.65 0.00 0.00 1.36 0.00 0.59 0.00 9.71
load the adehabitatHS library
library(adehabitatHS)
run the compana test on full data set (all 8 columns)
fulldata.comp <- compana(used.m, avail.m)
check result
fulldata.comp$test
Lambda P
NaN 1
now run compana on partial data (columns 1-7)
partdata.comp <- compana(used.m[, 1:7], avail.m[, 1:7])
check result
partdata.comp$test
Lambda P
0.3319731 0.6280000
