Burnham model - Missing Year/Cohort in Design data list

[gabrielbouleau]

Hi!

I have an issue when I try to build a Burnham model with LD data.

(Please note that the registration on the Phidot forum are closed, hence why I posted my issue here. Feel free to move it to the appropriate place)

When I build the ddl object, there seems to miss every other year in the Cohort/Year colums. This issue follows when building models and cause the PIMS matrices to have an extra parameters for the cohort missing.

See below a reproducible example with a subset of my data :

library(RMark)
#> This is RMark 2.2.7
#>  Documentation available at http://www.phidot.org/software/mark/rmark/RMarkDocumentation.zip

# Here is a subset of the first 10 years of the data
# The data have the format LDLDLD where L = capture/alive encounter
# and D = dead encounter. The column freq is this capture history
# frequency in the dataset

data <- tibble::tribble(
  ~ch, ~freq,
  "11000000000000000000", 1L,
  "10000000010000000000", 1L,
  "10000000000000000000", 3L,
  "00100000000100000000", 1L,
  "00100000000000000100", 1L,
  "00100000000000000000", 3L,
  "00001000000000000000", 14L,
  "00000010000100000000", 1L,
  "00000010000000000100", 1L,
  "00000010000000000000", 8L,
  "00000000100001000000", 2L,
  "00000000100000010000", 1L,
  "00000000100000000100", 1L,
  "00000000100000000000", 13L,
  "00000000001000010000", 1L,
  "00000000001000000000", 10L,
  "00000000000011000000", 2L,
  "00000000000010010000", 1L,
  "00000000000010000100", 1L,
  "00000000000010000000", 17L,
  "00000000000000101000", 1L,
  "00000000000000100100", 1L,
  "00000000000000100000", 13L,
  "00000000000000001000", 16L,
  "00000000000000000011", 2L,
  "00000000000000000010", 16L
)

# Process data into a Burnham life-dead model
data.proc <- process.data(
  data = data,
  model = "Burnham",
  begin.time = 1960
)

# Create design data list
data.ddl <- make.design.data(data.proc,
  remove.unused = T
)

# Where chekcing the desing data list, we notice that half
# the years are missing from the table. Upon running the model,
# this create a problem in the PIMS matrix
unique(data.ddl$S$Cohort)
#> [1] 0 2 4 6 8
data.ddl$S
#>    par.index model.index group cohort age time occ.cohort Cohort Age Time
#> 1          1           1     1   1960   0 1960          1      0   0    0
#> 2          2           2     1   1960   1 1961          1      0   1    1
#> 3          3           3     1   1960   2 1962          1      0   2    2
#> 4          4           4     1   1960   3 1963          1      0   3    3
#> 5          5           5     1   1960   4 1964          1      0   4    4
#> 6          6           6     1   1960   5 1965          1      0   5    5
#> 7          7           7     1   1960   6 1966          1      0   6    6
#> 8          8           8     1   1960   7 1967          1      0   7    7
#> 9          9           9     1   1960   8 1968          1      0   8    8
#> 10        10          10     1   1960   9 1969          1      0   9    9
#> 20        20          20     1   1962   0 1962          3      2   0    2
#> 21        21          21     1   1962   1 1963          3      2   1    3
#> 22        22          22     1   1962   2 1964          3      2   2    4
#> 23        23          23     1   1962   3 1965          3      2   3    5
#> 24        24          24     1   1962   4 1966          3      2   4    6
#> 25        25          25     1   1962   5 1967          3      2   5    7
#> 26        26          26     1   1962   6 1968          3      2   6    8
#> 27        27          27     1   1962   7 1969          3      2   7    9
#> 35        35          35     1   1964   0 1964          5      4   0    4
#> 36        36          36     1   1964   1 1965          5      4   1    5
#> 37        37          37     1   1964   2 1966          5      4   2    6
#> 38        38          38     1   1964   3 1967          5      4   3    7
#> 39        39          39     1   1964   4 1968          5      4   4    8
#> 40        40          40     1   1964   5 1969          5      4   5    9
#> 46        46          46     1   1966   0 1966          7      6   0    6
#> 47        47          47     1   1966   1 1967          7      6   1    7
#> 48        48          48     1   1966   2 1968          7      6   2    8
#> 49        49          49     1   1966   3 1969          7      6   3    9
#> 53        53          53     1   1968   0 1968          9      8   0    8
#> 54        54          54     1   1968   1 1969          9      8   1    9

^{Created on 2021-01-28 by the reprex package (v1.0.0)}

Session info

sessioninfo::session_info()
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#>  language (EN)                        
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#>  tz       America/New_York            
#>  date     2021-01-28                  
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