Catch at Age and Residuals

Catch-at-age observed data and model residuals from Icelandic saithe assessment.

catch.d
catch.r

Format

Data frame containing three columns:

`Year`	year
`Age`	age
and	`Catch`
catch (thousands of individuals)	or
`Resid`	standardized residual

Details

The data are from Tables 8.2 and 8.6 in the ICES (2015) fish stock assessment of Icelandic saithe.

Source

ICES (2015) Report of the North-Western Working Group (NWWG). ICES CM 2015/ACOM:07, pp. 240–246.

Examples

catch.t <- xtabs(Catch~Year+Age, catch.d)
catch.m <- as.matrix(as.data.frame(unclass(catch.t)))

# 1  Formula
bubbleplot(Catch~Age+Year, data=catch.d)

# Use rev=TRUE to get same layout as crosstab matrix:
print(catch.m)
#>         3     4    5     6     7    8    9   10  11  12  13  14
#> 1980  275  2540 5214  2596  2169 1341  387  262 155 112  64  33
#> 1981  203  1325 3503  5404  1457 1415  578  242  61 154 135 128
#> 1982  508  1092 2804  4845  4293 1215  975  306  59  35  48  46
#> 1983  107  1750 1065  2455  4454 2311  501  251  38  12   2   4
#> 1984   53   657  800  1825  2184 3610  844  376 291 135 185 226
#> 1985  376  4014 3366  1958  1536 1172  747  479  74  23  72  71
#> 1986 3108  1400 4170  2665  1550 1116  628 1549 216  51  30  14
#> 1987  956  5135 4428  5409  2915 1348  661  496 498  58  27  48
#> 1988 1318  5067 6619  3678  2859 1775  845  226 270 107  24   1
#> 1989  315  4313 8471  7309  1794 1928  848  270 191 135  76  10
#> 1990  143  1692 5471 10112  6174 1816 1087  380 151  55  76  37
#> 1991  198   874 3613  6844 10772 3223  858  838 228  40   6   5
#> 1992  242  2928 3844  4355  3884 4046 1290  350 196  56  54  15
#> 1993  657  1083 2841  2252  2247 2314 3671  830 223 188  81  12
#> 1994  702  2955 1770  2603  1377 1243 1263 2009 454 158 188  82
#> 1995 1573  1853 2661  1807  2370  905  574  482 521 106  35  13
#> 1996 1102  2608 1868  1649   835 1233  385  267 210 232 141  74
#> 1997  603  2960 2766  1651  1178  599  454  125  95 114  77  43
#> 1998  183  1289 1767  1545  1114  658  351  265 120  81  85  85
#> 1999  989   732 1564  2176  1934  669  324  140  72  25  28  22
#> 2000  850  2383  896  1511  1612 1806  335  173  57  33  17   7
#> 2001 1223  2619 2184   591   977  943  819  186  94  28  28  13
#> 2002 1187  4190 3147  2970   519  820  570  309 101  27  15  11
#> 2003 2284  4363 6031  2472  1942  285  438  289 196  28  29  15
#> 2004  952  7841 7195  5363  1563 1057  211  224 157  74  39  11
#> 2005 2607  3089 7333  6876  3592  978  642  119 149  89  46  12
#> 2006 1380 10051 2616  5840  4514 1989  667  485 118 112  86  31
#> 2007 1244  6552 8751  2124  2935 1817  964  395 190  43  36  20
#> 2008 1432  3602 5874  6706  1155 1894 1248  803 262 176  87  44
#> 2009 2820  5166 2084  2734  2883  777 1101  847 555 203 134  36
#> 2010 2146  6284 3058   997  1644 1571  514  656 522 231 114  64
#> 2011 2004  4850 4006  1502   677 1065 1145  323 433 244 150  75
#> 2012 1183  4816 3514  2417   903  432  883 1015 354 277 173  99
#> 2013 1163  5538 6366  2963  1610  664  375  537 460 124 118  78
#> 2014  668  3499 4867  2805  1276  725  347  241 312 199 128  74
bubbleplot(Catch~Age+Year, data=catch.d, rev=TRUE, las=1)


# 2  Data frame
bubbleplot(catch.d)


# 3  Matrix or table
bubbleplot(catch.m)

bubbleplot(catch.t)


# 4  Positive and negative values
bubbleplot(catch.r)

bubbleplot(Resid~Age+Year, catch.r, subset=Age %in% 4:9,
           rev=TRUE, xlim=c(3.5,9.5), cex=1.3)

Format

Details

Source

See also

Examples