### Data used for sperm whale analysis of Moore and Barlow, file edited 2 March 2014  ###

### Note -- format below is for calling OpenBUGS from R.  If pasting this file directly in to OpenBUGS, array formats need slight modification (remove function "t" or "aperm" before "structure" and switch values of .Dim argument) 


bugs.data <- list(
  
  W = 5.5,  	# Truncation distance (km) (note W is capitalized)
  
  T = c(1,3,6,11,15,18),	# value = true year - 1991 + 1
  
  nStrata = 4,  # number of geographic strata
  
  # stratum areas (SoCal, central, NoCal, ORWA)
  A = c(318541, 242959, 258070, 322237),
  
  nYrs = 6,   # number of survey years of data

  allYrs = 26,  # 1991 - 2014  (last 8 years are projections)
  
  # observed transect length in each stratum-year
  # vector lists all elements in row 1, then in row 2, etc
  L = t(structure(
    .Data = c(4040, 2627, 3994, 2455, 2837, 3034,
              2967, 1523, 3056, 1608, 2385, 2894,
              3018, 2085, 3287, 2376, 2665, 2396,
                0,     0, 4337, 3098, 2951, 3237),
    .Dim = c(6,4))),		# rows (strata) x columns (years)
  
  # Amount of effort in each Beaufort state, by j,t  (rows=strata, columns=yrs, each matrix is a beaufort class)
  Lb = aperm(structure(
      .Data=c(              # Matrix for Beaufort 0-1 effort in each j,t
             270,16,107,27,74,121,
             243,195,194,34,2,147,
             285,151,294,89,150,89,
             0,0,190,115,27,117,

                            # Matrix for Beaufort 2 effort in each j,t
             471,364,318,104,474,410,
             381,200,267,331,36,402,
             646,468,378,268,424,165,
             0,0,342,265,393,390,
             
                            # Matrix for Beaufort 3 effort in each j,t
             689,661,1008,415,583,531,
             628,530,810,321,450,330,
             778,661,717,255,555,316,
             0,0,1009,553,659,469,
             
                            # Matrix for Beaufort 4 effort in each j,t
             1950,875,1431,1109,1114,873,
             1164,363,1120,658,1335,1260,
             1055,522,1088,1118,823,821,
             0,0,1507,1605,1142,1222,
             
                            # Matrix for Beaufort 5 effort in each j,t
             660,711,1130,801,592,1099,
             552,235,666,264,568,755,
             254,284,810,646,712,1004,
             0,0,1288,560,731,1039),
      .Dim = c(6,4,5))),  # years, strata, no. Beaufort states  (dim of array in R is bft classes(5), strata(4), yrs(6) )
  
  # number groups detected in each stratum-year (row1=SC, row2=CC, row3=NC, row4=OW), by group size class
  n = aperm(structure(
    .Data = c(4,0,2,0,2,1,  # small groups (1 or 2 animals)
              0,0,1,1,0,3,
              0,1,1,3,7,3,
              0,0,1,1,3,3,
              
              7,1,1,4,1,1, # large groups (> 2 animals)
              2,4,2,0,0,0,
              0,7,2,1,7,2,
              0,0,3,1,1,0),
    .Dim = c(6,4,2))),  # dim of array in R is 2,4,6
  
  #Ngrps = 84,		# number of data records
  
  y = c(		# detection distances
    0.96,
    2.09,
    1.39,
    1.73,
    0.28,
    1.85,
    2.06,
    0.16,
    2.73,
    0.36,
    4.3,
    4.5,
    2.59,
    3.63,
    4.74,
    4.93,
    4.46,
    0.61,
    4,
    4.89,
    4.62,
    1.24,
    0.86,
    4.53,
    3.9,
    2.88,
    0.78,
    4.18,
    2.52,
    0.28,
    4.08,
    0.97,
    4.12,
    1.24,
    4.67,
    3.79,
    0.27,
    0.39,
    1.14,
    0.74,
    0,
    1.54,
    1.28,
    2.64,
    2.42,
    0.42,
    2,
    2.34,
    3.76,
    3.51,
    3.22,
    0.3,
    4.03,
    4.12,
    1.38,
    0.96,
    1.84,
    0.67,
    0.48,
    3.31,
    0.19,
    0.41,
    1.99,
    2.59,
    0.57,
    3.75,
    0,
    3.41,
    4.47,
    1.16,
    0.65,
    4.29,
    0.73,
    1.81,
    4.65,
    2.39,
    0,
    1.11,
    1.59,
    2.25,
    2.84,
    4.42,
    1.15,
    4.45),
  
  # dummy variable for years when group size needs correction
  m = c(1,1,1,0,0,0),
  
  # group (cluster) sizes
  
  cs = c(
    1,
    1.7,
    9.7,
    3.7,
    1,
    1,
    3.2,
    5.2,
    13.3,
    4,
    9,
    3.6,
    3.5,
    4.5,
    2.3,
    2.3,
    6,
    3.5,
    1,
    3,
    10.8,
    19.7,
    8,
    22,
    10,
    18,
    17.3,
    7.5,
    3.5,
    2,
    1,
    12,
    3.4,
    14,
    4,
    3,
    1,
    1,
    2,
    36.4,
    12.6,
    24.3,
    1,
    1.3,
    1,
    1,
    3,
    12.4,
    4.5,
    1.2,
    1,
    1,
    1,
    22.7,
    11.4,
    2.1,
    11.4,
    20.9,
    1,
    1,
    1,
    1,
    29.8,
    1,
    2,
    23.1,
    14.3,
    15.3,
    1,
    1,
    1,
    1,
    1,
    1,
    1,
    1,
    2,
    1,
    1,
    3.3,
    4,
    1,
    1,
    37.2),
  
  # records for which group size is > 2
  lgGrp.idx = c(3,  4,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 34, 35, 36, 40, 41, 42, 47, 48, 49, 54, 55, 56, 57, 58, 63, 66, 67, 68, 80, 81, 84),
  
  nLgGrps = 47,
  
  # records for which group size is <= 2
  smGrp.idx = c(1,  2,  5,  6, 19, 30, 31, 37, 38, 39, 43, 44, 45, 46, 50, 51, 52, 53, 59, 60, 61, 62, 64, 65, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 82, 83),
  
  nSmGrps = 37,
  
  # from winbugs file 'FBK 4km - data - covars'
  
  # columns
  # 1. RegionIndex,
  # 2 SoCal,
  # 3 CenCal,
  # 4 NoCal,
  # 5 ORWA,
  # 6 Year,
  # 7 YrTrend (year - 1991 + 1)
  # 8 YrIndex (1 = 1991, 2 = 1993, 3 = 1996, 4 = 2001, 5 = 2005, 6 = 2008
  # 9 dv91,
  # 10 dv93,
  # 11 dv96,
  #12 dv01,
  # 13 dv05,
  # 14 dv08,
  # 15 shipMAC
  # 16 shipDSJ,
  # 17 shipMc2,
  # 18 Cue,
  # 19 Bino,
  # 20 SwellHt
  # 21 RainFog,
  # 22 Glare,
  # 23 Closing,
  # 24 Beauf,
  # 25 Vis,
  # 26 vis.adj,
  
  covars = t(structure(
    .Data = c(
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,6,0,4,0,0,1,4,8,6,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,6,1,4,0,0,1,4,8,6,
      2,0,1,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,6,0,4,1,1,1,2,2,2,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,3,0,1.5,1,0,1,0,7,6,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,6,0,2.5,0,0,1,1,8,6,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,3,0,3,0,1,1,3,10,6,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,6,0,3,0,1,1,2,10,6,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,3,0,3,0,1,1,2,8,6,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,6,0,5,0,1,1,3,10,6,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,6,0,5,0,1,1,3,10,6,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,3,0,5,0,1,1,3,10,6,
      1,1,0,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,6,0,5,0,0,1,2,10,6,
      2,0,1,0,0,1991,1,1,1,0,0,0,0,0,1,0,0,6,0,6,0,0,1,4,9,6,
      2,0,1,0,0,1993,3,2,0,1,0,0,0,0,1,0,0,6,0,5,0,0,1,2,8,6,
      2,0,1,0,0,1993,3,2,0,1,0,0,0,0,1,0,0,6,0,5,0,0,1,2,8,6,
      2,0,1,0,0,1993,3,2,0,1,0,0,0,0,1,0,0,2,0,5,0,0,1,2,8,6,
      2,0,1,0,0,1993,3,2,0,1,0,0,0,0,1,0,0,6,0,6,0,0,1,2,9,6,
      3,0,0,1,0,1993,3,2,0,1,0,0,0,0,1,0,0,6,0,5,0,0,1,4,8,6,
      3,0,0,1,0,1993,3,2,0,1,0,0,0,0,1,0,0,6,0,5,0,0,1,5,9,6,
      1,1,0,0,0,1993,3,2,0,1,0,0,0,0,1,0,0,6,0,3,0,0,1,3,9,6,
      3,0,0,1,0,1993,3,2,0,1,0,0,0,0,1,0,0,6,0,4,0,0,1,3,8,6,
      3,0,0,1,0,1993,3,2,0,1,0,0,0,0,1,0,0,3,0,3,0,0,1,2,5,5,
      3,0,0,1,0,1993,3,2,0,1,0,0,0,0,1,0,0,6,0,3,1,0,1,2,5,5,
      3,0,0,1,0,1993,3,2,0,1,0,0,0,0,1,0,0,6,0,3,1,0,1,2,5,5,
      3,0,0,1,0,1993,3,2,0,1,0,0,0,0,1,0,0,3,0,3,1,0,1,2,5,5,
      3,0,0,1,0,1993,3,2,0,1,0,0,0,0,1,0,0,3,0,2,0,0,1,3,5,5,
      4,0,0,0,1,1996,6,3,0,0,1,0,0,0,1,0,0,6,0,4,1,0,0,3,4,4,
      4,0,0,0,1,1996,6,3,0,0,1,0,0,0,1,0,0,6,0,4,0,0,0,4,6,6,
      4,0,0,0,1,1996,6,3,0,0,1,0,0,0,1,0,0,6,0,8,0,1,1,5,5,5,
      4,0,0,0,1,1996,6,3,0,0,1,0,0,0,1,0,0,6,0,9,0,0,1,4,5,5,
      2,0,1,0,0,1996,6,3,0,0,1,0,0,0,1,0,0,6,0,3,0,0,1,3,5,5,
      1,1,0,0,0,1996,6,3,0,0,1,0,0,0,0,1,0,6,0,5,0,0,0,4,5,5,
      2,0,1,0,0,1996,6,3,0,0,1,0,0,0,0,1,0,6,0,4,0,0,1,2,5,5,
      2,0,1,0,0,1996,6,3,0,0,1,0,0,0,0,1,0,6,0,4,1,0,1,4,5,5,
      3,0,0,1,0,1996,6,3,0,0,1,0,0,0,0,1,0,6,0,5,0,1,0,5,6,6,
      3,0,0,1,0,1996,6,3,0,0,1,0,0,0,0,1,0,6,0,5,0,1,0,5,6,6,
      3,0,0,1,0,1996,6,3,0,0,1,0,0,0,0,1,0,6,0,5,0,1,0,5,6,6,
      1,1,0,0,0,1996,6,3,0,0,1,0,0,0,0,1,0,6,1,3,0,0,0,4,5,5,
      1,1,0,0,0,1996,6,3,0,0,1,0,0,0,0,1,0,6,0,3,0,0,1,4,5,5,
      1,1,0,0,0,2001,11,4,0,0,0,1,0,0,0,1,0,6,0,5,0,1,1,4,5,5,
      1,1,0,0,0,2001,11,4,0,0,0,1,0,0,0,1,0,6,0,5,0,0,1,4,6,6,
      1,1,0,0,0,2001,11,4,0,0,0,1,0,0,0,1,0,6,0,5,0,0,1,4,6,6,
      3,0,0,1,0,2001,11,4,0,0,0,1,0,0,0,1,0,3,0,3,1,0,1,4,3,3,
      3,0,0,1,0,2001,11,4,0,0,0,1,0,0,0,1,0,6,0,3,0,0,1,4,6,6,
      3,0,0,1,0,2001,11,4,0,0,0,1,0,0,0,1,0,6,0,8,0,1,1,1,6,6,
      4,0,0,0,1,2001,11,4,0,0,0,1,0,0,0,1,0,6,1,9,1,0,1,4,5,5,
      4,0,0,0,1,2001,11,4,0,0,0,1,0,0,0,1,0,3,0,8,0,0,1,5,6,6,
      3,0,0,1,0,2001,11,4,0,0,0,1,0,0,0,1,0,6,0,8,0,0,1,3,6,6,
      1,1,0,0,0,2001,11,4,0,0,0,1,0,0,1,0,0,6,0,6,0,0,1,4,6,6,
      2,0,1,0,0,2001,11,4,0,0,0,1,0,0,1,0,0,6,0,10,0,0,1,3,6,6,
      4,0,0,0,1,2005,15,5,0,0,0,0,1,0,0,0,1,6,0,4,0,0,1,5,5,5,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,0,1,6,0,4,0,0,1,2,7,6,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,0,1,6,0,4,0,0,0,1,7,6,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,0,1,6,0,3,1,0,1,3,5,5,
      1,1,0,0,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,5,0,0,1,4,6,6,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,4,0,0,1,5,6,6,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,6,0,0,1,5,5,5,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,5,0,0,1,5,5,5,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,3,0,0,1,3,6,6,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,3,0,0,1,4,6,6,
      4,0,0,0,1,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,3,0,0,1,4,6,6,
      4,0,0,0,1,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,5,0,0,1,5,3,3,
      4,0,0,0,1,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,3,0,1,1,3,4,4,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,1,3,0,0,1,3,6,6,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,5,0,0,1,5,5,5,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,3,0,0,1,3,4,4,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,3,0,0,1,4,6,6,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,5,0,0,1,4,6,6,
      3,0,0,1,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,0,3,1,0,1,4,5,5,
      1,1,0,0,0,2005,15,5,0,0,0,0,1,0,0,1,0,6,1,3,0,1,1,3,6,6,
      1,1,0,0,0,2005,15,5,0,0,0,0,1,0,0,1,0,2,1,4,0,0,1,4,5,5,
      4,0,0,0,1,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,5,0,1,1,4,7,6,
      4,0,0,0,1,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,7,0,0,1,5,7,6,
      4,0,0,0,1,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,3,0,1,1,2,6,6,
      3,0,0,1,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,1,3,0,0,1,2,7,6,
      3,0,0,1,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,3,0,0,1,4,7,6,
      3,0,0,1,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,3,1,0,1,5,4,4,
      1,1,0,0,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,7,0,0,1,4,7,6,
      2,0,1,0,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,4,1,0,1,3,4,4,
      3,0,0,1,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,4,0,0,1,5,7,6,
      3,0,0,1,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,4,0,0,1,5,7,6,
      2,0,1,0,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,4,0,0,1,4,7,6,
      2,0,1,0,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,4,0,1,1,4,7,6,
      1,1,0,0,0,2008,18,6,0,0,0,0,0,1,0,0,1,6,0,6,0,0,1,3,7,6),
    .Dim = c(26,84)))
  
  
)