Error in X.p[which(!is.na(y)), , drop = FALSE] : subscript out of bounds

[Justin Biggerstaff]

Hello all,

I am having this error when I am trying to run a single-species, multi-season model. To my knowledge (based on comparisons to the vignette), my data formatting looks correct. I have three seasons, with three replicates per season, and 74 sites that were surveyed across these seasons. 

List of 4 $ y : int [1:74, 1:3, 1:3] 0 0 0 0 0 0 0 0 1 0 ... $ occ.covs:List of 34 ..$ TreeHeight22: num [1:74] 27.1 28 18.4 20.7 21.6 ... ..$ TreeHeight45: num [1:74] 25.4 26.9 18.9 21.8 23 ... ..$ TreeHeight68: num [1:74] 24.9 26.1 19.4 23.5 23 ... ..$ WetlandPro22: num [1:74] 0 0.0443 0 0 0 ... ..$ WetlandPro45: num [1:74] 0.00133 0.02903 0.01529 0 0 ... ..$ WetlandPro68: num [1:74] 0.0152 0.0322 0.0246 0 0.0117 ... ..$ StreamDen22 : num [1:74] 0 2.2872 0 0.0515 0 ... ..$ StreamDen45 : num [1:74] 0 1.68 0 0.29 0 ... ..$ StreamDen68 : num [1:74] 0.271 1.665 0 0.32 0.193 ... ..$ Art_ADT22 : int [1:74] 105000 8900 32000 74000 71000 160000 71000 120000 87000 29000 ... ..$ Art_ADT45 : int [1:74] 105000 107000 32000 74000 71000 160000 84000 132000 87000 29000 ... ..$ Art_ADT68 : int [1:74] 105000 107000 32000 74000 71000 160000 84000 132000 87000 29000 ... ..$ All_ADT22 : int [1:74] 105000 8900 32000 74000 71000 160000 71000 120000 87000 29000 ... ..$ All_ADT45 : int [1:74] 105000 107000 32000 74000 71000 160000 84000 132000 87000 29000 ... ..$ All_ADT68 : int [1:74] 105000 107000 32000 74000 71000 160000 84000 132000 87000 29000 ... ..$ OpenWater22 : num [1:74] 0 0.000943 0 0 0 ... ..$ OpenWater45 : num [1:74] 0 0.0031 0 0.00709 0 ... ..$ OpenWater68 : num [1:74] 0 0.00202 0 0.00462 0 ... ..$ LocDen_22 : num [1:74] 6.394 8.416 1.08 5.555 0.822 ... ..$ LocDen_45 : num [1:74] 6.151 9.092 1.453 3.968 0.332 ... ..$ LocDen_68 : num [1:74] 6.394 8.416 1.08 5.555 0.822 ... ..$ ForPro_22 : num [1:74] 0.389 0.464 0.706 0.22 0.596 ... ..$ ForPro_45 : num [1:74] 0.426 0.33 0.701 0.236 0.714 ... ..$ ForPro_68 : num [1:74] 0.428 0.296 0.741 0.305 0.735 ... ..$ EdDen22 : num [1:74] 25.9 31.1 23.1 24.5 21.9 ... ..$ EdDen45 : num [1:74] 28.3 29 19.1 25.1 20 ... ..$ EdDen68 : num [1:74] 29.6 26.1 16.2 25.4 18.9 ... ..$ ArtDen22 : num [1:74] 13.4 9.94 10.45 10.21 13.24 ... ..$ ArtDen45 : num [1:74] 15.19 9.37 10.99 11.66 15.36 ... ..$ ArtDen68 : num [1:74] 13.4 9.94 10.45 10.21 13.24 ... ..$ AllDen22 : num [1:74] 17.37 15.19 6.72 17.04 18.57 ... ..$ AllDen45 : num [1:74] 21.3 18.5 12.4 16 16.2 ... ..$ AllDen68 : num [1:74] 19.8 18.4 11.5 16.3 14.4 ... ..$ season : num [1:74, 1:3] 1 1 1 1 1 1 1 1 1 1 ... $ det.covs:List of 7 ..$ Temp : num [1:74, 1:3, 1:3] 23.4 11.3 9.4 13.9 13.3 15.2 23.7 23.5 13.5 7.1 ... ..$ Wind : int [1:74, 1:3, 1:3] 0 0 2 0 0 1 1 1 1 0 ... ..$ Cloud: int [1:74, 1:3, 1:3] 70 0 0 0 0 0 80 90 60 0 ... ..$ Date : int [1:74, 1:3, 1:3] 90 86 86 80 85 70 88 88 78 62 ... ..$ Time : int [1:74, 1:3, 1:3] 58 154 278 281 60 174 71 246 183 111 ... ..$ Noise: int [1:74, 1:3, 1:3] 1 1 1 1 1 1 1 1 1 1 ... ..$ Rain : int [1:74, 1:3, 1:3] 0 0 0 0 0 0 0 0 0 0 ... $ coords : chr [1:74, 1:2] "1698972" "1619551" "1629582" "1679108" ... ..- attr(*, "dimnames")=List of 2 .. ..$ : NULL .. ..$ : chr [1:2] "Easting" "Northing"

I am trying to run a tPGOcc model, with a very basic null occupancy and global detection model to determine which detection covariates may be important. Would anyone know how to fix this issue? 

[Justin Biggerstaff]

Nevermind, I fixed my issue. I looked into my datafile and saw that some detection covariates got shifted in data entry resulting in a survey where detection data was present for a survey that did not occur. After correcting this, the model ran. Leaving this post up just in case anyone in the future runs into the same problem.