Methods to compute various summary calculations (sum, mean, variance) over
selected dimensions of objects from any array-based classes
(e.g. FLQuant
). These methods return an object of the
same dimensions as the input but with length one in the dimension chosen
to operate along.
quantSums(x, ...) yearSums(x, ...) unitSums(x, ...) seasonSums(x, ...) areaSums(x, ...) iterSums(x, ...) dimSums(x, ...) quantMeans(x, ...) yearMeans(x, ...) unitMeans(x, ...) seasonMeans(x, ...) areaMeans(x, ...) iterMeans(x, ...) dimMeans(x, ...) quantVars(x, ...) yearVars(x, ...) unitVars(x, ...) seasonVars(x, ...) areaVars(x, ...) iterVars(x, ...) dimVars(x, ...) iterMedians(x, ...) iterCVs(x, ...) # S4 method for FLQuant quantSums(x, na.rm = TRUE) # S4 method for FLQuant yearSums(x, na.rm = TRUE) # S4 method for FLQuant unitSums(x, na.rm = TRUE) # S4 method for FLQuant seasonSums(x, na.rm = TRUE) # S4 method for FLQuant areaSums(x, na.rm = TRUE) # S4 method for FLQuant iterSums(x, na.rm = TRUE) # S4 method for FLQuant quantMeans(x, na.rm = TRUE) # S4 method for FLQuant yearMeans(x, na.rm = TRUE) # S4 method for FLQuant unitMeans(x, na.rm = TRUE) # S4 method for FLQuant seasonMeans(x, na.rm = TRUE) # S4 method for FLQuant areaMeans(x, na.rm = TRUE) # S4 method for FLQuant iterMeans(x, na.rm = TRUE) # S4 method for FLQuant iterMedians(x, na.rm = TRUE) # S4 method for FLQuant quantVars(x, na.rm = TRUE) # S4 method for FLQuant yearVars(x, na.rm = TRUE) # S4 method for FLQuant unitVars(x, na.rm = TRUE) # S4 method for FLQuant seasonVars(x, na.rm = TRUE) # S4 method for FLQuant areaVars(x, na.rm = TRUE) # S4 method for FLQuant iterVars(x, na.rm = TRUE) # S4 method for FLQuant iterCVs(x, na.rm = TRUE) # S4 method for FLQuantDistr yearSums(x, na.rm = TRUE) # S4 method for FLQuantDistr unitSums(x, na.rm = TRUE) # S4 method for FLQuantDistr seasonSums(x, na.rm = TRUE) # S4 method for FLQuantDistr areaSums(x, na.rm = TRUE) # S4 method for FLQuantDistr yearMeans(x, na.rm = TRUE) # S4 method for FLQuantDistr unitMeans(x, na.rm = TRUE) # S4 method for FLQuantDistr seasonMeans(x, na.rm = TRUE) # S4 method for FLQuantDistr areaMeans(x, na.rm = TRUE) # S4 method for FLQuantDistr iterMeans(x, na.rm = TRUE) # S4 method for FLQuantDistr iterMedians(x, na.rm = TRUE) # S4 method for FLQuantDistr quantVars(x, na.rm = TRUE) # S4 method for FLQuantDistr yearVars(x, na.rm = TRUE) # S4 method for FLQuantDistr unitVars(x, na.rm = TRUE) # S4 method for FLQuantDistr seasonVars(x, na.rm = TRUE) # S4 method for FLQuantDistr areaVars(x, na.rm = TRUE) # S4 method for FLQuantDistr iterVars(x, na.rm = TRUE) # S4 method for FLPar iterMeans(x, na.rm = TRUE) # S4 method for FLPar iterMedians(x, na.rm = TRUE) # S4 method for FLPar iterVars(x, na.rm = TRUE) # S4 method for FLPar iterSums(x, na.rm = TRUE)
This set of methods computes three different summaries (sum, mean and
variance) of an FLQuant
object along each of the six dimensions
(quant, year, unit, season, area, or iter). Medians and CVs can also be
computed along the sixth dimension, iter
.
These methods encapsulate a call to apply
with
the corresponding dimensions and function: mean
,
median
, var
, and
sum
, while iterCVs
are computed as
sqrt(iterVars) / iterMeans
.
In contrast with R standard behaviour, the sum of a dimension where all
elements are NA
will be NA
and not 0. See example below.
Methods working along the iter dimension are also defined for objects of class
FLPar
.
Methods to operate over the first dimension refer to it as the quant
dimension, regardless of the actual name used in the object.
quantSums(x), quantMeans(x), quantVars(x) yearSums(x), yearMeans(x), yearVars(x) unitSums(x), unitMeans(x), unitVars(x) seasonSums(x), seasonMeans(x), seasonVars(x) areaSums(x), areaMeans(x), areaVars(x) iterMeans(x), iterVars(x), iterMedians(x), iterSums(x) dimSums(x), dimMeans(x), dimVars(x)
#> An object of class "FLQuant" #> iters: 10 #> #> , , unit = 1, season = 1, area = 1 #> #> year #> age 1 2 3 4 #> all 0.280540(2.117) 0.424350(2.937) 0.237649(1.189) 0.460682(2.289) #> year #> age 5 6 7 8 #> all -0.247708(0.905) 0.030765(1.338) 0.766331(1.810) 0.121210(1.490) #> year #> age 9 10 #> all 1.520713(2.505) -0.284361(3.751) #> #> , , unit = 2, season = 1, area = 1 #> #> year #> age 1 2 3 4 #> all -0.545568(2.527) 0.751224(1.939) -0.373198(2.707) 0.596430(2.103) #> year #> age 5 6 7 8 #> all -1.825318(1.775) 0.167829(1.478) -0.182774(2.984) -1.256246(1.836) #> year #> age 9 10 #> all 0.136952(1.944) -0.091679(1.942) #> #> , , unit = 1, season = 2, area = 1 #> #> year #> age 1 2 3 4 #> all -1.065747(1.009) 0.030185(2.515) -0.542175(1.373) -0.110870(1.671) #> year #> age 5 6 7 8 #> all -0.327672(2.564) 0.238650(0.528) -0.371620(1.551) 0.021899(2.254) #> year #> age 9 10 #> all -0.598046(1.490) -1.323708(1.855) #> #> , , unit = 2, season = 2, area = 1 #> #> year #> age 1 2 3 4 #> all -0.847988(1.732) 0.717873(1.941) -0.283832(2.892) -0.627861(1.127) #> year #> age 5 6 7 8 #> all -1.261515(1.466) 0.881576(1.317) 0.198070(2.835) 0.544717(0.656) #> year #> age 9 10 #> all 0.948773(2.005) 0.636966(1.210) #> #> , , unit = 1, season = 1, area = 2 #> #> year #> age 1 2 3 4 #> all 0.038158(2.540) -0.248996(1.495) -1.553658(1.796) 0.173297(0.615) #> year #> age 5 6 7 8 #> all -0.469051(3.651) 1.525627(1.593) -1.182820(2.892) 0.232370(3.495) #> year #> age 9 10 #> all -0.085440(2.542) -0.895687(2.110) #> #> , , unit = 2, season = 1, area = 2 #> #> year #> age 1 2 3 4 #> all -0.400505(1.947) 1.039465(1.543) -0.444131(0.702) 0.767755(1.809) #> year #> age 5 6 7 8 #> all 1.611870(1.919) -0.203222(1.855) 1.153073(1.916) 0.825186(2.002) #> year #> age 9 10 #> all -0.314160(2.852) -0.456452(2.221) #> #> , , unit = 1, season = 2, area = 2 #> #> year #> age 1 2 3 4 #> all -0.566765(2.924) 0.670766(1.937) 0.293247(1.171) -0.636146(0.660) #> year #> age 5 6 7 8 #> all 1.351125(2.902) 0.514156(2.213) 0.791253(1.902) 0.980189(2.761) #> year #> age 9 10 #> all 0.958265(3.083) -0.611107(1.900) #> #> , , unit = 2, season = 2, area = 2 #> #> year #> age 1 2 3 4 #> all 0.553947(1.930) 1.039568(2.456) 0.678175(2.750) 0.232721(0.964) #> year #> age 5 6 7 8 #> all -0.271844(1.850) 1.155938(2.133) -1.418219(3.355) -0.990810(1.295) #> year #> age 9 10 #> all -0.133427(2.245) -0.072252(1.925) #> #> units: NAquantMeans(flq)#> An object of class "FLQuant" #> iters: 10 #> #> , , unit = 1, season = 1, area = 1 #> #> year #> age 1 2 3 4 #> all 0.0561080(0.423) 0.0848699(0.587) 0.0475298(0.238) 0.0921365(0.458) #> year #> age 5 6 7 8 #> all -0.0495415(0.181) 0.0061531(0.268) 0.1532663(0.362) 0.0242420(0.298) #> year #> age 9 10 #> all 0.3041426(0.501) -0.0568721(0.750) #> #> , , unit = 2, season = 1, area = 1 #> #> year #> age 1 2 3 4 #> all -0.1091136(0.505) 0.1502448(0.388) -0.0746396(0.541) 0.1192859(0.421) #> year #> age 5 6 7 8 #> all -0.3650637(0.355) 0.0335657(0.296) -0.0365548(0.597) -0.2512493(0.367) #> year #> age 9 10 #> all 0.0273905(0.389) -0.0183358(0.388) #> #> , , unit = 1, season = 2, area = 1 #> #> year #> age 1 2 3 4 #> all -0.2131494(0.202) 0.0060370(0.503) -0.1084350(0.275) -0.0221740(0.334) #> year #> age 5 6 7 8 #> all -0.0655345(0.513) 0.0477301(0.106) -0.0743241(0.310) 0.0043798(0.451) #> year #> age 9 10 #> all -0.1196092(0.298) -0.2647416(0.371) #> #> , , unit = 2, season = 2, area = 1 #> #> year #> age 1 2 3 4 #> all -0.1695977(0.346) 0.1435747(0.388) -0.0567663(0.578) -0.1255723(0.225) #> year #> age 5 6 7 8 #> all -0.2523031(0.293) 0.1763153(0.263) 0.0396140(0.567) 0.1089435(0.131) #> year #> age 9 10 #> all 0.1897546(0.401) 0.1273932(0.242) #> #> , , unit = 1, season = 1, area = 2 #> #> year #> age 1 2 3 4 #> all 0.0076316(0.508) -0.0497991(0.299) -0.3107316(0.359) 0.0346595(0.123) #> year #> age 5 6 7 8 #> all -0.0938103(0.730) 0.3051255(0.319) -0.2365640(0.578) 0.0464740(0.699) #> year #> age 9 10 #> all -0.0170880(0.508) -0.1791373(0.422) #> #> , , unit = 2, season = 1, area = 2 #> #> year #> age 1 2 3 4 #> all -0.0801010(0.389) 0.2078931(0.309) -0.0888262(0.140) 0.1535509(0.362) #> year #> age 5 6 7 8 #> all 0.3223740(0.384) -0.0406444(0.371) 0.2306145(0.383) 0.1650373(0.400) #> year #> age 9 10 #> all -0.0628320(0.570) -0.0912903(0.444) #> #> , , unit = 1, season = 2, area = 2 #> #> year #> age 1 2 3 4 #> all -0.1133529(0.585) 0.1341532(0.387) 0.0586493(0.234) -0.1272292(0.132) #> year #> age 5 6 7 8 #> all 0.2702249(0.580) 0.1028312(0.443) 0.1582505(0.380) 0.1960377(0.552) #> year #> age 9 10 #> all 0.1916529(0.617) -0.1222215(0.380) #> #> , , unit = 2, season = 2, area = 2 #> #> year #> age 1 2 3 4 #> all 0.1107895(0.386) 0.2079135(0.491) 0.1356350(0.550) 0.0465443(0.193) #> year #> age 5 6 7 8 #> all -0.0543687(0.370) 0.2311876(0.427) -0.2836438(0.671) -0.1981620(0.259) #> year #> age 9 10 #> all -0.0266854(0.449) -0.0144505(0.385) #> #> units: NAyearSums(flq)#> An object of class "FLQuant" #> iters: 10 #> #> , , unit = 1, season = 1, area = 1 #> #> year #> age 1 #> 1 -1.593544(2.21) #> 2 0.496294(3.72) #> 3 1.141419(2.19) #> 4 2.284237(2.85) #> 5 -1.255869(1.53) #> #> , , unit = 2, season = 1, area = 1 #> #> year #> age 1 #> 1 -0.053495(4.18) #> 2 -0.653946(3.78) #> 3 -1.977494(3.86) #> 4 0.393789(1.88) #> 5 0.318747(1.01) #> #> , , unit = 1, season = 2, area = 1 #> #> year #> age 1 #> 1 -0.294134(2.21) #> 2 -1.382688(3.71) #> 3 -0.824558(4.16) #> 4 -1.857493(2.32) #> 5 0.755294(3.50) #> #> , , unit = 2, season = 2, area = 1 #> #> year #> age 1 #> 1 1.859258(1.33) #> 2 -0.652897(2.15) #> 3 1.562005(2.28) #> 4 0.422901(4.01) #> 5 -1.435617(4.19) #> #> , , unit = 1, season = 1, area = 2 #> #> year #> age 1 #> 1 -1.723989(2.73) #> 2 0.188767(1.90) #> 3 -1.348485(2.02) #> 4 0.273108(5.84) #> 5 -0.404199(2.83) #> #> , , unit = 2, season = 1, area = 2 #> #> year #> age 1 #> 1 0.946208(2.80) #> 2 1.767090(1.82) #> 3 -1.791587(3.43) #> 4 0.398337(1.17) #> 5 1.336210(3.45) #> #> , , unit = 1, season = 2, area = 2 #> #> year #> age 1 #> 1 1.050345(1.60) #> 2 0.334645(4.32) #> 3 0.926550(2.53) #> 4 0.065267(3.52) #> 5 0.756244(1.85) #> #> , , unit = 2, season = 2, area = 2 #> #> year #> age 1 #> 1 2.267494(2.83) #> 2 1.944274(7.79) #> 3 0.401304(1.42) #> 4 -1.155582(2.85) #> 5 -2.202864(1.72) #> #> units: NAiterMeans(flq)#> An object of class "FLQuant" #> , , unit = 1, season = 1, area = 1 #> #> year #> age 1 2 3 4 5 6 #> 1 0.1928159 -0.0695767 0.3195847 -0.1084254 -0.1538952 0.1577127 #> 2 0.1703859 0.3583441 0.2657940 -0.4958943 -0.1281008 0.1429765 #> 3 -0.2751938 -0.1340555 0.0433412 0.1027628 0.9183433 -0.2828716 #> 4 0.1349799 0.0489651 -0.3123700 0.2003846 0.1611073 0.1883190 #> 5 -0.2391113 -0.2001921 -0.1534936 0.6134129 -1.0080015 -0.1659071 #> year #> age 7 8 9 10 #> 1 -0.5246124 -0.1732292 -0.1139285 0.0238212 #> 2 -0.0742776 0.0637401 0.3955672 -0.3631186 #> 3 0.3965150 -0.0912937 0.3205946 -0.0124865 #> 4 0.1376135 0.3788341 0.5247406 -0.1898197 #> 5 0.4235011 -0.2593276 -0.3557802 0.2745077 #> #> , , unit = 2, season = 1, area = 1 #> #> year #> age 1 2 3 4 5 6 #> 1 0.1307720 0.4907945 -0.1887352 0.5271031 -0.3614746 -0.4025924 #> 2 0.0693708 -0.6081555 -0.0784352 -0.1304509 0.0275625 -0.2987451 #> 3 -0.3834444 -0.2839389 -0.3785923 0.0517353 -0.8609419 0.0067336 #> 4 0.0802087 0.0307193 0.1059786 0.1926397 -0.0455259 -0.1643695 #> 5 0.2267195 0.4146621 -0.1148075 -0.4345475 -0.3760642 0.2887213 #> year #> age 7 8 9 10 #> 1 -0.3458558 -0.2655661 0.2715690 0.1529457 #> 2 -0.2582429 0.1831258 0.1133968 -0.3918602 #> 3 0.1308282 -0.7460923 -0.2527359 0.5852523 #> 4 0.0370705 -0.5283720 0.0287130 -0.3659408 #> 5 0.3156270 -0.0412978 0.0590814 0.0508110 #> #> , , unit = 1, season = 2, area = 1 #> #> year #> age 1 2 3 4 5 6 #> 1 -0.0890564 0.2137073 0.1861893 -0.0930322 0.0519958 0.0739023 #> 2 -0.1259435 -0.1431168 -0.4314814 0.1808095 -0.1870820 -0.1372758 #> 3 0.2267733 0.0720291 -0.0375682 -0.1067446 0.0039738 -0.5662254 #> 4 -0.8665722 -0.2308985 0.0141496 0.0978762 0.0173640 -0.2219022 #> 5 -0.3377576 0.0169082 0.5575117 0.2560404 0.2207232 0.5720257 #> year #> age 7 8 9 10 #> 1 -0.4670702 -0.2107292 0.3134729 -0.5599599 #> 2 -0.2782532 0.0678338 -0.0797529 -0.2164396 #> 3 -0.0685683 0.5519040 -0.2296863 -0.2354308 #> 4 0.5498830 -0.1890184 -0.1684973 -0.2900389 #> 5 -0.1460617 0.1098861 -0.1919484 -0.2087982 #> #> , , unit = 2, season = 2, area = 1 #> #> year #> age 1 2 3 4 5 6 #> 1 0.3999219 0.1783551 -0.4253604 0.0899592 0.1898800 -0.0222863 #> 2 -0.2058181 0.2496775 -0.1931609 -0.2414402 -0.5165791 0.3325149 #> 3 0.2980406 0.1453390 0.0757813 -0.3032418 -0.1231402 0.1472886 #> 4 -0.5946953 0.4740882 0.1744544 0.0418515 0.4846675 -0.0231418 #> 5 -0.4594045 -0.4865070 0.0386282 0.2997709 -0.5590456 0.2774929 #> year #> age 7 8 9 10 #> 1 0.3844138 0.7221640 -0.2403035 0.1119153 #> 2 -0.4325390 0.0314522 0.1384342 0.1992611 #> 3 0.3630872 0.1657385 0.4437133 0.5497824 #> 4 0.0182983 -0.1881656 -0.2042901 0.0756519 #> 5 -0.0114183 -0.2148852 0.1960490 -0.0874604 #> #> , , unit = 1, season = 1, area = 2 #> #> year #> age 1 2 3 4 5 6 #> 1 0.1209742 0.0937805 -0.2050742 -0.3685312 -0.3457985 0.0968025 #> 2 -0.0977949 0.0469322 -0.3430022 0.3453793 0.4137527 0.1864857 #> 3 -0.1197231 -0.3701452 -0.0898393 0.2142980 0.1318026 -0.3520410 #> 4 0.1199108 0.0200070 0.2076049 0.1556289 -0.1380161 0.3775640 #> 5 -0.1648849 -0.1083915 -0.4995403 0.3788716 -0.0252614 0.0857068 #> year #> age 7 8 9 10 #> 1 -0.3521480 0.2922619 0.3873843 -0.2375751 #> 2 0.3562573 -0.0178318 0.1579715 -0.5803682 #> 3 -0.3821228 0.1010759 -0.1020338 -0.0450457 #> 4 -0.1751546 0.2292294 0.1545400 0.2753249 #> 5 -0.0456659 0.0418818 -0.1322343 0.1831033 #> #> , , unit = 2, season = 1, area = 2 #> #> year #> age 1 2 3 4 5 6 #> 1 -0.2874226 0.7011886 0.3693614 0.0128933 0.4451882 -0.1056922 #> 2 0.2779898 0.3198802 -0.1291725 0.0979766 0.0155628 -0.1336020 #> 3 0.0216189 -0.1334800 -0.4182594 0.2242716 0.4196391 0.0095931 #> 4 0.3499197 0.1979582 -0.3834070 0.3512735 -0.0045455 -0.4442737 #> 5 -0.1562935 -0.0093466 0.3395124 -0.3312899 -0.0271958 0.1416709 #> year #> age 7 8 9 10 #> 1 0.0159866 0.1913505 -0.2775442 0.2703775 #> 2 0.0474680 0.9565255 0.4748001 0.0698462 #> 3 -0.2297476 0.0674540 -0.3803067 -0.0887457 #> 4 0.6397115 -0.1266166 -0.1717058 -0.0992357 #> 5 0.5133478 -0.3505933 0.0077145 0.0997242 #> #> , , unit = 1, season = 2, area = 2 #> #> year #> age 1 2 3 4 5 6 #> 1 -0.4080584 0.1651630 0.0704376 0.2702951 0.5740949 0.3943833 #> 2 -0.1815677 0.0362370 0.0603004 -0.4117141 0.1512594 -0.3279487 #> 3 0.2375162 0.3017998 0.1577338 -0.5049128 -0.2919400 -0.0529479 #> 4 -0.4493239 -0.0018777 -0.5529986 0.0017538 0.4052981 0.6344365 #> 5 0.0507364 -0.2636108 0.3583810 0.1102655 0.2721283 0.4347514 #> year #> age 7 8 9 10 #> 1 0.2841129 0.6129058 -0.4063153 -0.6168130 #> 2 -0.1638842 0.5272589 0.0339541 0.0432598 #> 3 0.2576942 0.1675610 0.3541931 -0.0965615 #> 4 0.2277811 -0.6226028 0.1658223 0.2607365 #> 5 -0.0737488 -0.1485793 0.5776591 -0.1153451 #> #> , , unit = 2, season = 2, area = 2 #> #> year #> age 1 2 3 4 5 6 #> 1 0.5869519 -0.5489555 -0.0420914 0.0040940 0.4814616 -0.0959803 #> 2 0.2619177 0.7006886 0.4399788 -0.3528248 0.6426112 0.2703026 #> 3 0.4777380 0.4751232 -0.0704623 0.1677468 0.1305230 0.2122314 #> 4 -0.1792835 0.1203405 -0.0715355 -0.0831309 -0.1567766 0.1887961 #> 5 -0.0647772 0.2667392 -0.1898742 0.3310626 -0.4038957 0.3634217 #> year #> age 7 8 9 10 #> 1 -0.0140634 0.0999905 0.4347874 0.2386336 #> 2 -0.1625534 0.5092286 0.0782052 0.0203002 #> 3 -0.2308461 -0.7615388 -0.1483321 0.1409138 #> 4 -0.3418889 -0.1166411 -0.1424690 -0.1112922 #> 5 -0.2973028 -0.6404182 -0.1450712 -0.1448703 #> #> units: NAdim(quantSums(flq))#> [1] 1 10 2 2 2 10# NA dims stay as NA when summed along x <- FLQuant(c(NA, NA, NA, rnorm(6)), dim=c(3, 3)) quantSums(x)#> An object of class "FLQuant" #> , , unit = unique, season = all, area = unique #> #> year #> quant 1 2 3 #> all NA -0.88334 -0.48824 #> #> units: NA# although in fact a sum of no elements (as na.rm=TRUE) is zero apply(x, 2:6, sum, na.rm=TRUE)#> An object of class "FLQuant" #> , , unit = unique, season = all, area = unique #> #> year #> quant 1 2 3 #> all 0.00000 -0.88334 -0.48824 #> #> units: NA