residuals
Usage
# S4 method for class 'FLQuant'
residuals(object, fit, type = "log", ...)Examples
data(ple4)
fit <- rlnorm(1, log(catch(ple4)), 0.1)
residuals(catch(ple4), fit)
#> An x of class "FLQuant"
#> , , unit = unique, season = all, area = unique
#>
#> year
#> age 1957 1958 1959 1960 1961 1962 1963 1964
#> all -0.01088 -0.05897 0.00440 0.16864 0.05521 -0.02818 0.12303 -0.15887
#> year
#> age 1965 1966 1967 1968 1969 1970 1971 1972
#> all 0.11787 -0.05337 0.21659 0.04447 0.11465 -0.05696 0.03405 -0.14882
#> year
#> age 1973 1974 1975 1976 1977 1978 1979 1980
#> all -0.08716 0.08932 0.08204 -0.13662 0.16609 -0.14959 -0.10571 0.10784
#> year
#> age 1981 1982 1983 1984 1985 1986 1987 1988
#> all 0.07161 -0.07494 0.10196 0.12662 -0.00593 -0.00646 0.09392 0.12820
#> year
#> age 1989 1990 1991 1992 1993 1994 1995 1996
#> all 0.05468 0.01215 -0.05187 0.04224 0.09154 0.01149 -0.16232 0.05590
#> year
#> age 1997 1998 1999 2000 2001 2002 2003 2004
#> all -0.07177 0.12636 0.24957 -0.15671 0.12689 -0.12813 0.04263 -0.12922
#> year
#> age 2005 2006 2007 2008 2009 2010 2011 2012
#> all -0.06870 -0.07510 -0.09803 -0.01307 0.05499 -0.10868 0.10604 0.01379
#> year
#> age 2013 2014 2015 2016 2017
#> all -0.04387 0.12811 0.08117 0.12019 0.01763
#>
#> units: t
residuals(catch(ple4), fit, type="student")
#> An x of class "FLQuant"
#> , , unit = unique, season = all, area = unique
#>
#> year
#> age 1957 1958 1959 1960 1961 1962 1963 1964
#> all 0.36850 0.29522 0.22516 0.21273 0.15963 0.08805 0.06750 -0.02112
#> year
#> age 1965 1966 1967 1968 1969 1970 1971 1972
#> all 0.02352 0.00264 0.02297 0.01706 0.04213 0.03149 0.04246 -0.01886
#> year
#> age 1973 1974 1975 1976 1977 1978 1979 1980
#> all -0.00746 0.00397 -0.00317 0.08568 -0.01103 0.11179 0.05161 0.02577
#> year
#> age 1981 1982 1983 1984 1985 1986 1987 1988
#> all 0.04458 0.22100 0.27505 0.48618 1.40956 2.96838 4.08078 4.23652
#> year
#> age 1989 1990 1991 1992 1993 1994 1995 1996
#> all 3.31275 1.47231 0.65768 0.12092 0.01491 0.00855 0.00499 0.09207
#> year
#> age 1997 1998 1999 2000 2001 2002 2003 2004
#> all -0.00526 -0.00921 -0.03113 -0.02000 0.13621 -0.00985 0.00753 -0.00319
#> year
#> age 2005 2006 2007 2008 2009 2010 2011 2012
#> all 0.13483 0.14771 0.17987 0.16720 0.18257 0.09162 0.17855 0.07652
#> year
#> age 2013 2014 2015 2016 2017
#> all 0.02098 0.07391 0.07249 0.11630 0.11377
#>
#> units:
rraw(catch(ple4), fit)
#> An x of class "FLQuant"
#> , , unit = unique, season = all, area = unique
#>
#> year
#> age 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966
#> all -857 -5393 462 18308 6421 -3609 16302 -25403 16834 -8895
#> year
#> age 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976
#> all 30082 6516 15834 -8008 4727 -23972 -13799 13500 13027 -25749
#> year
#> age 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
#> all 25380 -28749 -19252 18881 12750 -14976 20612 27149 -1470 -1810
#> year
#> age 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996
#> all 27654 37930 15540 3026 -11616 7970 15709 1728 -23374 7161
#> year
#> age 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
#> all -11324 20326 37693 -24769 15267 -19658 6428 -19320 -8147 -8724
#> year
#> age 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
#> all -10791 -1492 6191 -13642 12045 1806 -6325 16804 10708 14860
#> year
#> age 2017
#> all 2184
#>
#> units: t
rlogstandard(catch(ple4), fit)
#> An x of class "FLQuant"
#> , , unit = unique, season = all, area = unique
#>
#> year
#> age 1957 1958 1959 1960 1961 1962 1963 1964 1965
#> all -0.1060 -0.5744 0.0428 1.6426 0.5378 -0.2745 1.1984 -1.5474 1.1481
#> year
#> age 1966 1967 1968 1969 1970 1971 1972 1973 1974
#> all -0.5198 2.1097 0.4331 1.1167 -0.5548 0.3316 -1.4496 -0.8490 0.8700
#> year
#> age 1975 1976 1977 1978 1979 1980 1981 1982 1983
#> all 0.7991 -1.3308 1.6178 -1.4571 -1.0297 1.0504 0.6975 -0.7300 0.9932
#> year
#> age 1984 1985 1986 1987 1988 1989 1990 1991 1992
#> all 1.2334 -0.0578 -0.0629 0.9148 1.2487 0.5326 0.1183 -0.5053 0.4114
#> year
#> age 1993 1994 1995 1996 1997 1998 1999 2000 2001
#> all 0.8917 0.1119 -1.5811 0.5445 -0.6990 1.2308 2.4309 -1.5264 1.2360
#> year
#> age 2002 2003 2004 2005 2006 2007 2008 2009 2010
#> all -1.2480 0.4152 -1.2587 -0.6692 -0.7315 -0.9548 -0.1273 0.5356 -1.0586
#> year
#> age 2011 2012 2013 2014 2015 2016 2017
#> all 1.0329 0.1343 -0.4273 1.2478 0.7907 1.1707 0.1718
#>
#> units:
rstandard(catch(ple4), fit)
#> An x of class "FLQuant"
#> , , unit = unique, season = all, area = unique
#>
#> year
#> age 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968
#> all 9.45 9.01 9.60 11.31 10.10 9.29 10.80 8.15 10.75 9.06 11.86 9.99
#> year
#> age 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980
#> all 10.71 9.02 9.88 8.23 8.76 10.45 10.37 8.33 11.28 8.23 8.60 10.64
#> year
#> age 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992
#> all 10.26 8.86 10.58 10.84 9.50 9.49 10.49 10.86 10.09 9.67 9.07 9.97
#> year
#> age 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
#> all 10.47 9.66 8.12 10.10 8.89 10.84 12.26 8.17 10.85 8.40 9.97 8.40
#> year
#> age 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
#> all 8.92 8.86 8.66 9.43 10.09 8.57 10.62 9.69 9.14 10.86 10.36 10.77
#> year
#> age 2017
#> all 9.72
#>
#> units:
rstudent(catch(ple4), fit)
#> An x of class "FLQuant"
#> , , unit = unique, season = all, area = unique
#>
#> year
#> age 1957 1958 1959 1960 1961 1962 1963 1964
#> all 0.36850 0.29522 0.22516 0.21273 0.15963 0.08805 0.06750 -0.02112
#> year
#> age 1965 1966 1967 1968 1969 1970 1971 1972
#> all 0.02352 0.00264 0.02297 0.01706 0.04213 0.03149 0.04246 -0.01886
#> year
#> age 1973 1974 1975 1976 1977 1978 1979 1980
#> all -0.00746 0.00397 -0.00317 0.08568 -0.01103 0.11179 0.05161 0.02577
#> year
#> age 1981 1982 1983 1984 1985 1986 1987 1988
#> all 0.04458 0.22100 0.27505 0.48618 1.40956 2.96838 4.08078 4.23652
#> year
#> age 1989 1990 1991 1992 1993 1994 1995 1996
#> all 3.31275 1.47231 0.65768 0.12092 0.01491 0.00855 0.00499 0.09207
#> year
#> age 1997 1998 1999 2000 2001 2002 2003 2004
#> all -0.00526 -0.00921 -0.03113 -0.02000 0.13621 -0.00985 0.00753 -0.00319
#> year
#> age 2005 2006 2007 2008 2009 2010 2011 2012
#> all 0.13483 0.14771 0.17987 0.16720 0.18257 0.09162 0.17855 0.07652
#> year
#> age 2013 2014 2015 2016 2017
#> all 0.02098 0.07391 0.07249 0.11630 0.11377
#>
#> units: