I am trying to analyse bird detection probability using the package 'Distance' in R. I split up detection by bird size class: small and medium.large based on weight because individual species detections were low. Below is for small bird size class across 26 different sites, that varied in 4 different habitat types: ag, forest, shrubland, grassland. I have higher but decent AIC values with some of my outputs (Ex 1) and the lower AIC value formulas gives NA and null outputs(Example 2). Trying to troubleshoot and figure out what is wrong. Veg type= category, mean annual rainfall= continuous. I have also included my output without any variables (Example 3). Is it not possible to use a continuous variable as a factor? Because the outputs have low AIC’s with NA’s and nulls (Example 4). I appreciate any guidance or recommendation. Thank you in advance!
> head(det_small3)
Region.Label Sample.Label Effort distance size Species vegheight canopy weight meanannualrainfall elevation ground avgtempf vegtype
1 agriculture 5 1 35 15 small 0.35 0 17.9 409.9 31.09 80 78 agriculture
2 agriculture 5 1 40 6 small 0.35 0 17.9 409.9 31.09 80 78 agriculture
3 agriculture 5 1 45 4 small 0.35 0 17.9 409.9 31.09 80 78 agriculture
4 agriculture 5 1 40 5 small 0.35 0 17.9 409.9 31.09 80 78 agriculture
5 agriculture 5 1 45 10 small 0.35 0 17.9 409.9 31.09 80 78 agriculture
6 agriculture 5 1 30 2 small 0.35 0 17.9 409.9 31.09 80 78 agriculture
> tail(det_small3)
Region.Label Sample.Label Effort distance size Species vegheight canopy weight meanannualrainfall elevation ground avgtempf vegtype
237 grassland 26 1 60 30 small 0.7 0 17.9 1249.7 341 70 73.0 grassland
238 grassland 26 1 40 3 small 0.7 0 17.9 1249.7 341 70 73.0 grassland
239 grassland 26 1 70 3 small 0.7 0 17.9 1249.7 341 70 73.0 grassland
240 grassland 26 1 80 2 small 0.7 0 17.9 1249.7 341 70 73.0 grassland
241 grassland 26 1 30 3 small 0.7 0 17.9 1249.7 341 70 73.0 grassland
242 shrubland 15 1 NA NA small 0.5 0 na 1177.5 2673 50 52.9 shrubland
dput(det_small3)structure(list(Region.Label = structure(c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L), .Label = c("agriculture",
"forest", "shrubland", "grassland"), class = "factor"), Area = c(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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Sample.Label = structure(c(5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 13L,
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 19L, 21L, 21L, 21L,
21L, 21L, 21L, 21L, 21L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L,
23L, 23L, 23L, 23L, 23L, 23L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 9L, 9L, 9L, 9L, 9L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 18L, 18L, 18L, 20L, 20L, 20L, 20L, 24L, 24L, 24L, 24L,
24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 24L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 22L, 22L, 22L, 22L, 22L, 22L, 3L, 3L, 3L, 3L, 3L,
4L, 4L, 4L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
8L, 14L, 14L, 14L, 14L, 17L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L, 25L,
25L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 15L), .Label = c("1",
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13",
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24",
"25", "26"), class = "factor"), Effort = c(1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1), distance = c(35, 40, 45, 40, 45, 30, 45, 75,
55, 65, 80, 50, 50, 10, 30, 20, 30, 20, 30, 40, 150, 30, 40,
10, 10, 15, 20, 20, 30, 50, 20, 40, 25, 30, 30, 50, 50, 20, 20,
20, 40, 5, 20, 20, 20, 20, 30, 5, 10, 30, 20, 10, 30, 20, 10,
30, 15, 20, 25, 10, 20, 40, 15, 20, 30, 40, 20, 30, 30, 30, 30,
30, 100, 30, 30, 30, 10, 40, 30, 60, 90, 40, 80, 40, 30, 45,
15, 20, 70, 80, 60, 30, 100, 80, 50, 40, 60, 30, 30, 40, 60,
70, 55, 35, 40, 50, 45, 40, 45, 35, 35, 30, 40, 10, 6, 10, 5,
15, 20, 30, 15, 40, 20, 25, 20, 30, 40, 20, 25, 15, 30, 25, 30,
30, 25, 20, 20, 25, 50, 40, 50, 30, 50, 50, 50, 30, 60, 60, 80,
60, 80, 30, 100, 60, 25, 50, 30, 20, 30, 40, 20, 30, 20, 30,
50, 40, 30, 40, 30, 20, 30, 60, 50, 20, 50, 55, 35, 55, 15, 30,
10, 50, 60, 80, 40, 35, 35, 50, 40, 30, 25, 30, 50, 50, 40, 30,
50, 50, 30, 200, 200, 100, 100, 100, 150, 100, 30, 40, 30, 20,
70, 40, 40, 60, 60, 30, 50, 50, 30, 50, 60, 80, 90, 30, 60, 80,
40, 100, 50, 40, 35, 20, 60, 90, 40, 50, 60, 40, 70, 80, 30,
NA), size = c(15, 6, 4, 5, 10, 2, 2, 4, 2, 10, 3, 3, 3, 3, 11,
2, 2, 1, 2, 6, 4, 2, 1, 6, 2, 8, 2, 2, 1, 3, 2, 3, 2, 5, 2, 6,
6, 14, 6, 2, 4, 2, 2, 2, 5, 4, 5, 2, 4, 12, 1, 8, 3, 3, 12, 4,
2, 6, 6, 6, 2, 7, 2, 8, 10, 1, 14, 2, 3, 1, 2, 2, 3, 2, 2, 4,
3, 4, 2, 8, 1, 4, 1, 2, 8, 15, 8, 5, 9, 8, 2, 2, 3, 2, 8, 2,
1, 3, 2, 2, 2, 5, 4, 3, 7, 6, 3, 1, 6, 4, 1, 3, 1, 5, 4, 3, 4,
3, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 1, 2, 5, 2, 1, 2, 3, 3, 9,
8, 5, 2, 2, 2, 2, 2, 3, 4, 6, 4, 2, 2, 3, 2, 2, 6, 1, 1, 1, 1,
1, 4, 2, 6, 1, 1, 4, 4, 2, 3, 3, 3, 8, 2, 3, 4, 2, 4, 1, 1, 2,
1, 1, 1, 1, 2, 10, 4, 4, 2, 10, 3, 3, 2, 5, 6, 2, 2, 2, 1, 5,
2, 1, 2, 1, 1, 1, 6, 4, 4, 4, 2, 2, 2, 2, 3, 2, 2, 3, 3, 2, 8,
2, 1, 2, 2, 1, 2, 2, 3, 6, 1, 8, 3, 12, 10, 15, 30, 3, 3, 2,
3, NA), Species = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("medium.large",
"small", "raptor"), class = "factor"), vegheight = c(0.35, 0.35,
0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.35, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.4, 0.4, 0.4, 0.4,
0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4,
0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4,
0.4, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25,
0.25, 0.25, 0.25, 0.25, 0.25, 0.725, 0.725, 0.725, 0.725, 0.725,
0.725, 0.725, 0.725, 0.725, 0.725, 0.45, 0.45, 0.45, 0.45, 0.45,
0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 0.45,
0.45, 0.45, 0.45, 0.45, 0.45, 0.45, 2.93, 2.93, 2.93, 9, 9, 9,
9, 9, 9, 9, 9, 9, 9, 5, 5, 5, 5, 5, 20, 20, 20, 20, 20, 20, 20,
20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 0.4, 0.4,
0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 6, 6,
6, 0.5, 0.5, 0.5, 0.5, 8.3, 8.3, 8.3, 8.3, 8.3, 8.3, 8.3, 8.3,
8.3, 8.3, 8.3, 8.3, 8.3, 0.3, 0.3, 0.43, 0.43, 0.43, 0.43, 0.43,
0.55, 0.55, 0.55, 0.55, 0.55, 0.55, 0.55, 0.55, 0.55, 0.55, 0.55,
0.2, 0.2, 0.2, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.11, 0.11, 0.11, 0.11, 0.3, 0.15, 0.15,
0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15,
0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.7, 0.7, 0.7,
0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.5), canopy = c(0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 5, 5, 5, 5,
5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
5, 5, 5, 5, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 85, 85, 85, 90,
90, 90, 90, 90, 90, 90, 90, 90, 90, 60, 60, 60, 60, 60, 75, 75,
75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75,
75, 75, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 65, 65, 65, 0,
0, 0, 0, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65,
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, 10, 10, 10, 10, 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), weight = structure(c(1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L), .Label = c("17.9",
"na"), class = "factor"), meanannualrainfall = c(409.9, 409.9,
409.9, 409.9, 409.9, 409.9, 409.9, 409.9, 409.9, 409.9, 409.9,
467.5, 467.5, 467.5, 467.5, 467.5, 467.5, 467.5, 467.5, 467.5,
467.5, 306.8, 306.8, 306.8, 306.8, 306.8, 306.8, 306.8, 306.8,
306.8, 306.8, 306.8, 306.8, 306.8, 306.8, 306.8, 306.8, 306.8,
306.8, 306.8, 306.8, 306.8, 306.8, 306.8, 306.8, 306.8, 306.8,
306.8, 306.8, 306.8, 306.8, 306.8, 306.8, 320.7, 320.7, 320.7,
320.7, 320.7, 320.7, 320.7, 320.7, 320.7, 320.7, 320.7, 320.7,
320.7, 320.7, 320.7, 409.9, 409.9, 409.9, 409.9, 409.9, 409.9,
409.9, 409.9, 409.9, 409.9, 376.6, 376.6, 376.6, 376.6, 376.6,
376.6, 376.6, 376.6, 352.4, 352.4, 352.4, 352.4, 352.4, 352.4,
352.4, 352.4, 352.4, 352.4, 352.4, 352.4, 352.4, 352.4, 2044.1,
2044.1, 2044.1, 918.3, 918.3, 918.3, 918.3, 918.3, 918.3, 918.3,
918.3, 918.3, 918.3, 2004.5, 2004.5, 2004.5, 2004.5, 2004.5,
1842.8, 1842.8, 1842.8, 1842.8, 1842.8, 1842.8, 1842.8, 1842.8,
1842.8, 1842.8, 1842.8, 1842.8, 1842.8, 1842.8, 1842.8, 1842.8,
1842.8, 1842.8, 1842.8, 1842.8, 808, 808, 808, 808, 808, 808,
808, 808, 808, 808, 808, 808, 808, 3550.6, 3550.6, 3550.6, 797.7,
797.7, 797.7, 797.7, 1352.1, 1352.1, 1352.1, 1352.1, 1352.1,
1352.1, 1352.1, 1352.1, 1352.1, 1352.1, 1352.1, 1352.1, 1352.1,
1008, 1008, 1008, 1008, 1008, 1008, 1008, 1012.9, 1012.9, 1012.9,
1012.9, 1012.9, 1012.9, 634.4, 634.4, 634.4, 634.4, 634.4, 1371,
1371, 1371, 734.2, 734.2, 734.2, 734.2, 734.2, 734.2, 734.2,
734.2, 734.2, 734.2, 734.2, 734.2, 734.2, 734.2, 525.8, 525.8,
525.8, 525.8, 718.9, 677.8, 677.8, 677.8, 677.8, 677.8, 677.8,
677.8, 677.8, 677.8, 677.8, 677.8, 677.8, 677.8, 677.8, 677.8,
677.8, 677.8, 677.8, 677.8, 677.8, 677.8, 1249.7, 1249.7, 1249.7,
1249.7, 1249.7, 1249.7, 1249.7, 1249.7, 1249.7, 1177.5), elevation = c(31.09,
31.09, 31.09, 31.09, 31.09, 31.09, 31.09, 31.09, 31.09, 31.09,
31.09, 335.28, 335.28, 335.28, 335.28, 335.28, 335.28, 335.28,
335.28, 335.28, 335.28, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11,
11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11,
11, 11, 11, 11, 11, 11, 78.02, 78.02, 78.02, 78.02, 78.02, 78.02,
78.02, 78.02, 78.02, 78.02, 78.02, 78.02, 78.02, 78.02, 78.02,
52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 182, 182, 182, 182, 182,
182, 182, 182, 44, 44, 44, 44, 44, 44, 44, 44, 44, 44, 44, 44,
44, 44, 27.13, 27.13, 27.13, 1981.2, 1981.2, 1981.2, 1981.2,
1981.2, 1981.2, 1981.2, 1981.2, 1981.2, 1981.2, 746.76, 746.76,
746.76, 746.76, 746.76, 1981.2, 1981.2, 1981.2, 1981.2, 1981.2,
1981.2, 1981.2, 1981.2, 1981.2, 1981.2, 1981.2, 1981.2, 1981.2,
1981.2, 1981.2, 1981.2, 1981.2, 1981.2, 1981.2, 1981.2, 1433,
1433, 1433, 1433, 1433, 1433, 1433, 1433, 1433, 1433, 1433, 1433,
1433, 73, 73, 73, 1343, 1343, 1343, 1343, 396, 396, 396, 396,
396, 396, 396, 396, 396, 396, 396, 396, 396, 1828.8, 1828.8,
2194.56, 2194.56, 2194.56, 2194.56, 2194.56, 2569, 2569, 2569,
2569, 2569, 2569, 502.92, 502.92, 502.92, 502.92, 502.92, 944.88,
944.88, 944.88, 667.5, 667.5, 667.5, 667.5, 667.5, 667.5, 667.5,
667.5, 667.5, 667.5, 667.5, 667.5, 667.5, 667.5, 359.05, 359.05,
359.05, 359.05, 986, 690, 690, 690, 690, 690, 690, 690, 690,
690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690, 690,
341, 341, 341, 341, 341, 341, 341, 341, 341, 2673), ground = c(80,
80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 70, 70, 70, 70, 70, 70,
70, 70, 70, 70, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50,
50, 50, 50, 50, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75, 75,
75, 75, 75, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 75, 75, 75,
75, 75, 75, 75, 75, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70, 70,
70, 70, 70, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95,
90, 90, 90, 90, 90, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80,
80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80,
80, 80, 80, 80, 80, 80, 95, 95, 95, 73, 73, 73, 73, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 80, 80,
60, 60, 60, 60, 60, 40, 40, 40, 40, 40, 40, 85, 85, 85, 85, 85,
95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95, 95,
95, 35, 35, 35, 35, 75, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65,
65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 70, 70, 70, 70, 70,
70, 70, 70, 70, 50), avgtempf = c(78, 78, 78, 78, 78, 78, 78,
78, 78, 78, 78, 77.5, 77.5, 77.5, 77.5, 77.5, 77.5, 77.5, 77.5,
77.5, 77.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5,
80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5,
80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5, 80.5,
80.5, 79.5, 79.5, 79.5, 79.5, 79.5, 79.5, 79.5, 79.5, 79.5, 79.5,
79.5, 79.5, 79.5, 79.5, 79.5, 80.6, 80.6, 80.6, 80.6, 80.6, 80.6,
80.6, 80.6, 80.6, 80.6, 78.4, 78.4, 78.4, 78.4, 78.4, 78.4, 78.4,
78.4, 77, 77, 77, 77, 77, 77, 77, 77, 77, 77, 77, 77, 77, 77,
76, 76, 76, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 68.5, 68.5,
68.5, 68.5, 68.5, 54.3, 54.3, 54.3, 54.3, 54.3, 54.3, 54.3, 54.3,
54.3, 54.3, 54.3, 54.3, 54.3, 54.3, 54.3, 54.3, 54.3, 54.3, 54.3,
54.3, 65.5, 65.5, 65.5, 65.5, 65.5, 65.5, 65.5, 65.5, 65.5, 65.5,
65.5, 65.5, 65.5, 74.5, 74.5, 74.5, 65, 65, 65, 65, 78, 78, 78,
78, 78, 78, 78, 78, 78, 78, 78, 78, 78, 65, 65, 65, 65, 65, 65,
65, 50, 50, 50, 50, 50, 50, 69, 69, 69, 69, 69, 66, 66, 66, 65.8,
65.8, 65.8, 65.8, 65.8, 65.8, 65.8, 65.8, 65.8, 65.8, 65.8, 65.8,
65.8, 65.8, 74.3, 74.3, 74.3, 74.3, 67.4, 75.5, 75.5, 75.5, 75.5,
75.5, 75.5, 75.5, 75.5, 75.5, 75.5, 75.5, 75.5, 75.5, 75.5, 75.5,
75.5, 75.5, 75.5, 75.5, 75.5, 75.5, 73, 73, 73, 73, 73, 73, 73,
73, 73, 52.9), vegtype = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L), .Label = c("agriculture",
"forest", "shrubland", "grassland"), class = "factor")), class = "data.frame", row.names = c(NA,
-242L))
Example 1:
detect_hrvegtype$dht$individuals$summary
Region Area CoveredArea Effort n ER se.ER cv.ER mean.size se.mean
1 agriculture 198470.1 198470.1 7 428 61.14286 13.698155 0.2240352 4.412371 0.3501204
2 forest 198470.1 226823.0 8 206 25.75000 5.936419 0.2305405 2.942857 0.2162026
3 shrubland 198470.1 113411.5 4 31 7.75000 2.954516 0.3812279 2.384615 0.5608883
4 grassland 198470.1 198470.1 7 216 30.85714 10.479978 0.3396289 4.408163 0.6912465
5 Total 793880.5 737174.7 26 881 33.88462 5.961241 0.1759276 3.847162 0.2262063
Example 2:
detect_hrcosmeanannualrainfall$dht$individuals$summary NULL
summary(detect_hrcosmeanannualrainfall)
Summary for distance analysis
Number of observations : 229
Distance range : 0 - 95
Model : Hazard-rate key function
AIC : 6
Detection function parameters
Scale coefficient(s):
estimate se
(Intercept) 3.108856 NA
meanannualrainfall -1.000038 NA
Shape coefficient(s):
estimate se
(Intercept) 0.8765737 NA
Estimate SE CV
Average p 0 NA NA
N in covered region Inf NA NA
Example 3:
summary(detect_hrcos)
Summary for distance analysis
Number of observations : 229
Distance range : 0 - 95
Model : Hazard-rate key function
AIC : 1954.596
Detection function parameters
Scale coefficient(s):
estimate se
(Intercept) 3.645371 0.06451175
Shape coefficient(s):
estimate se
(Intercept) 1.461591 0.1104191
Estimate SE CV
Average p 0.2519536 0.02109612 0.0837302
N in covered region 908.8975475 92.14143419 0.1013771
Summary for clusters
Summary statistics:
Region Area CoveredArea Effort n k ER se.ER cv.ER
1 agriculture 198470.1 198470.1 7 97 7 13.857143 3.165503 0.2284383
2 forest 198470.1 226823.0 8 70 8 8.750000 2.234071 0.2553224
3 shrubland 198470.1 113411.5 4 13 4 3.250000 1.376893 0.4236593
4 grassland 198470.1 198470.1 7 49 7 7.000000 2.380476 0.3400680
5 Total 793880.5 737174.7 26 229 26 8.807692 1.406599 0.1597012
Density:
Label Estimate se cv lcl ucl df
1 agriculture 0.0019397960 0.0004719521 0.2432999 0.0011118509 0.003384274 7.716770
2 forest 0.0012248712 0.0003291242 0.2687010 0.0006710625 0.002235722 8.583516
3 shrubland 0.0004549522 0.0001964729 0.4318541 0.0001286891 0.001608384 3.238871
4 grassland 0.0009798970 0.0003431836 0.3502242 0.0004357316 0.002203646 6.748863
5 Total 0.0011498791 0.0001921382 0.1670942 0.0008205686 0.001611348 33.532371
Summary for individuals
Summary statistics:
Region Area CoveredArea Effort n ER se.ER cv.ER mean.size se.mean
1 agriculture 198470.1 198470.1 7 428 61.14286 13.698155 0.2240352 4.412371 0.3501204
2 forest 198470.1 226823.0 8 206 25.75000 5.936419 0.2305405 2.942857 0.2162026
3 shrubland 198470.1 113411.5 4 31 7.75000 2.954516 0.3812279 2.384615 0.5608883
4 grassland 198470.1 198470.1 7 216 30.85714 10.479978 0.3396289 4.408163 0.6912465
5 Total 793880.5 737174.7 26 881 33.88462 5.961241 0.1759276 3.847162 0.2262063
Density:
Label Estimate se cv lcl ucl df
1 agriculture 0.008559100 0.0020470844 0.2391705 0.0049557369 0.014782502 7.789194
2 forest 0.003604621 0.0008841224 0.2452747 0.0020857164 0.006229654 8.963693
3 shrubland 0.001084886 0.0004234468 0.3903146 0.0003470734 0.003391149 3.296311
4 grassland 0.004319546 0.0015109678 0.3497979 0.0019226637 0.009704492 6.750856
5 Total 0.004392038 0.0007439172 0.1693786 0.0031064619 0.006209636 25.098525
Expected cluster size
Region Expected.S se.Expected.S cv.Expected.S
1 agriculture 4.412371 0.3659490 0.08293704
2 forest 2.942857 0.2285997 0.07767953
3 shrubland 2.384615 0.8192792 0.34356868
4 grassland 4.408163 1.1686187 0.26510331
5 Total 3.819565 0.3229394 0.08454874
Example 4:
detect_hrcoselevation<- ds(det_small3, truncation = 95, transect = "point", key = "hr", formula =
~elevation) #AIC=-382
detect_hrcosmeanannualrainfall<- ds(det_small3, truncation = 95, transect = "point", key = "hr", formula = ~meanannualrainfall) #AIC=6
detect_hrcosmeanannualrainfallvegheight<- ds(det_small3, truncation = 95, transect = "point", key = "hr", formula = ~meanannualrainfall+vegheight) #AIC=8
