Summaries by dimension
Source:R/genericMethods.R, R/FLQuant.R, R/FLQuantDistr.R, and 1 more
dimSummaries.RdMethods 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.
Usage
quantSums(x, ...)
yearSums(x, ...)
unitSums(x, ...)
seasonSums(x, ...)
areaSums(x, ...)
iterSums(x, ...)
dimSums(x, ...)
quantMeans(x, ...)
yearMedians(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, ...)
iterProb(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
yearMedians(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 FLQuant
iterProb(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)Details
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.
Generic methods
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)
Examples
flq <- FLQuant(rnorm(4000), dim=c(5,10,2,2,2,10), quant='age')
quantSums(flq)
#> An object of class "FLQuant"
#> iters: 10
#>
#> , , unit = 1, season = 1, area = 1
#>
#> year
#> age 1 2 3 4
#> all -1.476721(2.606) -0.332862(2.154) -0.937370(2.784) -0.680696(2.203)
#> year
#> age 5 6 7 8
#> all -0.403291(2.466) -0.861787(1.673) -0.033123(3.440) -0.067224(1.501)
#> year
#> age 9 10
#> all 1.210317(2.962) -0.827674(4.459)
#>
#> , , unit = 2, season = 1, area = 1
#>
#> year
#> age 1 2 3 4
#> all -0.023503(1.951) 0.947065(1.837) 1.182005(3.496) -0.084561(1.860)
#> year
#> age 5 6 7 8
#> all -0.248202(1.272) -0.790756(1.542) 1.060758(1.878) 1.031011(1.422)
#> year
#> age 9 10
#> all 0.695817(1.449) 1.139104(2.218)
#>
#> , , unit = 1, season = 2, area = 1
#>
#> year
#> age 1 2 3 4
#> all 0.372650(1.176) 0.610384(1.728) -0.381136(0.886) 0.657504(3.222)
#> year
#> age 5 6 7 8
#> all -0.418326(1.998) 0.341671(1.039) -0.908939(3.436) 0.598591(2.562)
#> year
#> age 9 10
#> all -1.080371(2.737) 0.310561(1.415)
#>
#> , , unit = 2, season = 2, area = 1
#>
#> year
#> age 1 2 3 4
#> all 0.808285(0.811) 0.920526(1.725) -0.831073(1.383) 2.157116(1.522)
#> year
#> age 5 6 7 8
#> all 0.949810(2.472) 0.781566(2.603) 0.224637(1.573) 0.496233(1.928)
#> year
#> age 9 10
#> all 0.825861(2.646) -0.238428(1.411)
#>
#> , , unit = 1, season = 1, area = 2
#>
#> year
#> age 1 2 3 4
#> all -0.381693(2.909) -0.095693(3.093) -0.293061(1.217) 0.020456(2.273)
#> year
#> age 5 6 7 8
#> all 0.092717(1.779) -1.124509(2.149) -0.826676(2.574) -0.024669(2.391)
#> year
#> age 9 10
#> all -0.865928(1.438) -0.682361(1.648)
#>
#> , , unit = 2, season = 1, area = 2
#>
#> year
#> age 1 2 3 4
#> all 0.207336(1.704) -1.646678(1.761) -0.534961(2.752) 1.354510(1.630)
#> year
#> age 5 6 7 8
#> all -0.622381(2.338) 1.236903(0.956) 0.386943(2.099) 0.042592(0.881)
#> year
#> age 9 10
#> all 0.298229(2.369) 0.063914(1.290)
#>
#> , , unit = 1, season = 2, area = 2
#>
#> year
#> age 1 2 3 4
#> all 0.187481(2.581) 1.167155(2.387) -0.020265(2.802) -0.415563(1.964)
#> year
#> age 5 6 7 8
#> all -0.301292(2.128) 1.054142(1.602) -0.523299(1.268) 1.267266(1.877)
#> year
#> age 9 10
#> all 1.333761(3.389) -0.508602(1.669)
#>
#> , , unit = 2, season = 2, area = 2
#>
#> year
#> age 1 2 3 4
#> all -0.129244(1.939) -0.713706(3.618) -0.244747(2.467) -0.201415(3.050)
#> year
#> age 5 6 7 8
#> all -0.974318(1.280) -0.073944(1.860) -1.223494(1.422) -0.870046(1.411)
#> year
#> age 9 10
#> all 0.270513(2.377) -0.250027(4.086)
#>
#> units: NA
quantMeans(flq)
#> An object of class "FLQuant"
#> iters: 10
#>
#> , , unit = 1, season = 1, area = 1
#>
#> year
#> age 1 2 3 4
#> all -0.2953442(0.521) -0.0665725(0.431) -0.1874740(0.557) -0.1361392(0.441)
#> year
#> age 5 6 7 8
#> all -0.0806582(0.493) -0.1723574(0.335) -0.0066246(0.688) -0.0134449(0.300)
#> year
#> age 9 10
#> all 0.2420633(0.592) -0.1655347(0.892)
#>
#> , , unit = 2, season = 1, area = 1
#>
#> year
#> age 1 2 3 4
#> all -0.0047006(0.390) 0.1894129(0.367) 0.2364010(0.699) -0.0169122(0.372)
#> year
#> age 5 6 7 8
#> all -0.0496404(0.254) -0.1581513(0.308) 0.2121516(0.376) 0.2062023(0.284)
#> year
#> age 9 10
#> all 0.1391634(0.290) 0.2278208(0.444)
#>
#> , , unit = 1, season = 2, area = 1
#>
#> year
#> age 1 2 3 4
#> all 0.0745300(0.235) 0.1220768(0.346) -0.0762271(0.177) 0.1315009(0.644)
#> year
#> age 5 6 7 8
#> all -0.0836652(0.400) 0.0683342(0.208) -0.1817878(0.687) 0.1197182(0.512)
#> year
#> age 9 10
#> all -0.2160743(0.547) 0.0621123(0.283)
#>
#> , , unit = 2, season = 2, area = 1
#>
#> year
#> age 1 2 3 4
#> all 0.1616570(0.162) 0.1841051(0.345) -0.1662147(0.277) 0.4314232(0.304)
#> year
#> age 5 6 7 8
#> all 0.1899621(0.494) 0.1563132(0.521) 0.0449275(0.315) 0.0992466(0.386)
#> year
#> age 9 10
#> all 0.1651723(0.529) -0.0476856(0.282)
#>
#> , , unit = 1, season = 1, area = 2
#>
#> year
#> age 1 2 3 4
#> all -0.0763387(0.582) -0.0191387(0.619) -0.0586123(0.243) 0.0040911(0.455)
#> year
#> age 5 6 7 8
#> all 0.0185433(0.356) -0.2249018(0.430) -0.1653352(0.515) -0.0049338(0.478)
#> year
#> age 9 10
#> all -0.1731857(0.288) -0.1364723(0.330)
#>
#> , , unit = 2, season = 1, area = 2
#>
#> year
#> age 1 2 3 4
#> all 0.0414672(0.341) -0.3293356(0.352) -0.1069922(0.550) 0.2709021(0.326)
#> year
#> age 5 6 7 8
#> all -0.1244762(0.468) 0.2473806(0.191) 0.0773885(0.420) 0.0085183(0.176)
#> year
#> age 9 10
#> all 0.0596459(0.474) 0.0127828(0.258)
#>
#> , , unit = 1, season = 2, area = 2
#>
#> year
#> age 1 2 3 4
#> all 0.0374962(0.516) 0.2334309(0.477) -0.0040530(0.560) -0.0831126(0.393)
#> year
#> age 5 6 7 8
#> all -0.0602585(0.426) 0.2108285(0.320) -0.1046598(0.254) 0.2534533(0.375)
#> year
#> age 9 10
#> all 0.2667523(0.678) -0.1017204(0.334)
#>
#> , , unit = 2, season = 2, area = 2
#>
#> year
#> age 1 2 3 4
#> all -0.0258488(0.388) -0.1427413(0.724) -0.0489494(0.493) -0.0402829(0.610)
#> year
#> age 5 6 7 8
#> all -0.1948636(0.256) -0.0147889(0.372) -0.2446989(0.284) -0.1740092(0.282)
#> year
#> age 9 10
#> all 0.0541027(0.475) -0.0500054(0.817)
#>
#> units: NA
yearSums(flq)
#> An object of class "FLQuant"
#> iters: 10
#>
#> , , unit = 1, season = 1, area = 1
#>
#> year
#> age 1
#> 1 -0.453046(2.683)
#> 2 -0.858712(2.835)
#> 3 1.262139(2.858)
#> 4 -0.517698(2.899)
#> 5 -2.574219(2.545)
#>
#> , , unit = 2, season = 1, area = 1
#>
#> year
#> age 1
#> 1 1.975911(2.332)
#> 2 -0.040903(1.468)
#> 3 1.329686(2.791)
#> 4 1.295434(3.968)
#> 5 0.234355(4.839)
#>
#> , , unit = 1, season = 2, area = 1
#>
#> year
#> age 1
#> 1 0.524242(2.618)
#> 2 0.343936(2.979)
#> 3 -1.180131(4.172)
#> 4 2.172125(1.202)
#> 5 0.315649(2.183)
#>
#> , , unit = 2, season = 2, area = 1
#>
#> year
#> age 1
#> 1 0.730413(5.109)
#> 2 1.652417(2.416)
#> 3 1.704377(2.837)
#> 4 -0.429285(1.851)
#> 5 1.239743(4.828)
#>
#> , , unit = 1, season = 1, area = 2
#>
#> year
#> age 1
#> 1 -0.745577(1.851)
#> 2 -1.893032(0.537)
#> 3 -1.696050(1.973)
#> 4 -0.770141(2.490)
#> 5 -0.065305(2.513)
#>
#> , , unit = 2, season = 1, area = 2
#>
#> year
#> age 1
#> 1 -0.241152(2.239)
#> 2 -1.450671(2.886)
#> 3 1.535035(2.570)
#> 4 0.572407(3.687)
#> 5 0.840019(3.356)
#>
#> , , unit = 1, season = 2, area = 2
#>
#> year
#> age 1
#> 1 -0.486389(3.589)
#> 2 -0.303532(2.371)
#> 3 0.058484(2.619)
#> 4 0.208881(0.725)
#> 5 3.688478(2.013)
#>
#> , , unit = 2, season = 2, area = 2
#>
#> year
#> age 1
#> 1 1.173944(5.532)
#> 2 -0.742442(4.742)
#> 3 -2.513914(4.532)
#> 4 -0.823072(2.642)
#> 5 -0.393057(1.958)
#>
#> units: NA
iterMeans(flq)
#> An object of class "FLQuant"
#> , , unit = 1, season = 1, area = 1
#>
#> year
#> age 1 2 3 4 5 6
#> 1 -2.5596e-02 -3.1421e-01 3.5796e-01 -2.8836e-01 -6.0114e-02 2.3703e-01
#> 2 3.0533e-02 4.8929e-03 1.1261e-01 1.9915e-02 -8.9331e-02 -2.7219e-01
#> 3 -2.8597e-01 -3.7785e-01 -3.2963e-01 1.2018e-01 1.2093e-02 1.1868e-01
#> 4 -4.9263e-01 2.8548e-01 -6.4398e-01 4.4132e-01 -1.9207e-01 -4.9117e-01
#> 5 -3.7096e-01 4.2715e-02 -1.5241e-01 -8.5655e-01 -4.2708e-01 -3.4140e-01
#> year
#> age 7 8 9 10
#> 1 7.2284e-02 1.1185e-05 2.0823e-01 -1.5669e-02
#> 2 -1.1729e-02 -6.4483e-01 6.3224e-01 -5.9165e-01
#> 3 2.4731e-01 1.6373e-01 3.7604e-01 3.6644e-01
#> 4 2.7047e-01 3.4008e-01 1.3205e-01 -2.7098e-01
#> 5 -5.5068e-01 -1.4055e-01 -3.5936e-02 -3.8283e-01
#>
#> , , unit = 2, season = 1, area = 1
#>
#> year
#> age 1 2 3 4 5 6
#> 1 3.5992e-02 1.4675e-01 1.5069e-01 -6.4208e-02 7.1639e-01 1.4233e-01
#> 2 4.0199e-01 -5.4621e-01 2.7121e-01 2.2613e-01 6.7918e-02 -3.0330e-01
#> 3 -5.6962e-02 1.2309e-01 -7.2679e-01 -2.5106e-01 6.3318e-01 4.4261e-02
#> 4 -1.8704e-01 3.5762e-01 2.1506e-01 1.4011e-01 8.8054e-02 2.1349e-01
#> 5 -1.3349e-01 4.5189e-01 3.4632e-01 1.7205e-01 -6.0728e-01 -2.4552e-01
#> year
#> age 7 8 9 10
#> 1 7.7198e-02 4.2300e-01 -3.0248e-01 1.8913e-01
#> 2 7.0998e-01 3.1157e-02 -2.8285e-01 -5.2359e-02
#> 3 2.8560e-01 8.4691e-02 5.2627e-01 3.0126e-01
#> 4 -1.5714e-01 6.4096e-01 -4.2187e-01 3.1421e-01
#> 5 2.0758e-01 3.3934e-01 -4.8025e-01 -3.0575e-01
#>
#> , , unit = 1, season = 2, area = 1
#>
#> year
#> age 1 2 3 4 5 6
#> 1 9.5079e-02 -4.4012e-01 -2.3057e-01 3.3224e-01 5.8890e-01 1.3670e-01
#> 2 -4.6010e-02 -1.3690e-01 4.4358e-01 9.3749e-02 -5.9642e-01 2.3588e-01
#> 3 -1.5972e-01 -1.0183e-01 -3.6836e-01 1.0896e-01 6.0380e-02 1.1044e-01
#> 4 8.6189e-02 4.5501e-01 -2.4297e-01 5.5829e-01 2.8685e-02 -3.2634e-02
#> 5 2.7655e-02 3.8286e-01 -2.6931e-01 -3.2403e-01 -6.8363e-01 9.4661e-02
#> year
#> age 7 8 9 10
#> 1 2.6424e-01 -2.1043e-03 8.0877e-02 4.8653e-01
#> 2 3.8072e-02 2.4654e-01 -9.5477e-02 -3.4334e-01
#> 3 -3.4377e-01 2.5481e-01 -8.4467e-02 -7.0995e-01
#> 4 5.0257e-02 3.4136e-01 2.6264e-02 2.6555e-01
#> 5 6.0273e-01 6.0633e-01 -1.7886e-01 2.3726e-01
#>
#> , , unit = 2, season = 2, area = 1
#>
#> year
#> age 1 2 3 4 5 6
#> 1 2.2382e-01 3.6807e-01 3.5981e-01 3.0160e-01 3.0079e-01 -1.1940e-01
#> 2 -1.0586e-01 1.9730e-01 -2.0065e-01 3.2678e-01 1.1712e-01 4.8431e-01
#> 3 6.3326e-02 -5.7304e-01 -2.4050e-01 5.6148e-01 6.2491e-01 4.2937e-01
#> 4 -7.4662e-02 1.4374e-01 4.2017e-01 -1.1848e-01 1.7196e-01 5.0264e-02
#> 5 3.0282e-01 4.5473e-01 -7.1355e-03 1.5270e-01 -2.6724e-02 2.3033e-01
#> year
#> age 7 8 9 10
#> 1 -1.7526e-01 -1.3111e-02 1.8802e-01 -4.3040e-01
#> 2 -1.7377e-01 1.5901e-01 8.0099e-01 -8.3459e-02
#> 3 2.6809e-01 4.2213e-01 -3.0038e-01 3.5395e-02
#> 4 3.7460e-01 -9.0443e-03 1.8614e-01 -4.9214e-01
#> 5 -4.0226e-02 3.2100e-01 -1.9912e-01 5.8885e-02
#>
#> , , unit = 1, season = 1, area = 2
#>
#> year
#> age 1 2 3 4 5 6
#> 1 -1.0150e-01 3.4950e-02 -6.0169e-01 -7.1558e-02 -3.7815e-01 -3.0096e-02
#> 2 -2.6661e-01 1.9786e-01 2.2461e-02 5.8363e-02 -2.7297e-01 -7.5724e-01
#> 3 1.6199e-01 2.6556e-01 -1.1657e-01 -2.1499e-01 1.0515e-01 5.5607e-02
#> 4 2.4270e-01 -6.3726e-01 -3.8011e-01 5.3341e-01 3.1374e-01 -3.2178e-01
#> 5 1.6954e-01 -1.6001e-01 3.5186e-01 6.4553e-02 -3.7849e-03 9.1998e-02
#> year
#> age 7 8 9 10
#> 1 4.4574e-01 4.9337e-01 -7.4821e-02 -3.9503e-01
#> 2 1.9104e-01 -4.2562e-01 -3.9759e-01 -2.9641e-01
#> 3 -7.0967e-01 2.6751e-01 1.4274e-01 -8.7616e-01
#> 4 1.4026e-01 6.9314e-03 -1.6503e-01 5.1654e-02
#> 5 -1.9790e-01 -3.6281e-02 -4.3105e-01 -8.2133e-03
#>
#> , , unit = 2, season = 1, area = 2
#>
#> year
#> age 1 2 3 4 5 6
#> 1 -2.9862e-01 -4.5773e-01 -2.3659e-01 1.4961e-01 3.3329e-01 2.0133e-02
#> 2 3.4917e-01 -3.9025e-01 2.7194e-01 -5.5923e-01 -3.2817e-01 -3.6404e-03
#> 3 1.8983e-01 -3.3218e-01 -9.2659e-02 5.8883e-01 -7.7019e-02 2.9198e-01
#> 4 1.5424e-01 -4.3012e-02 -7.3499e-01 7.0200e-03 -2.2557e-01 1.4796e-01
#> 5 -6.2182e-01 5.8137e-02 -2.9609e-01 9.6969e-01 1.0009e-01 4.7719e-01
#> year
#> age 7 8 9 10
#> 1 2.3571e-01 -1.1497e-01 6.5258e-03 5.5506e-02
#> 2 1.5380e-01 4.7475e-02 -5.8833e-03 -3.2991e-01
#> 3 7.7053e-02 2.9167e-01 -2.4935e-02 -1.6871e-01
#> 4 1.3631e-01 3.3649e-01 2.3468e-01 3.9104e-01
#> 5 2.7294e-01 -5.7290e-01 1.0030e-01 1.3632e-01
#>
#> , , unit = 1, season = 2, area = 2
#>
#> year
#> age 1 2 3 4 5 6
#> 1 -2.1342e-01 7.1789e-01 -2.6289e-01 -5.2887e-01 -2.0141e-01 4.2307e-01
#> 2 2.6695e-02 -6.6024e-02 -1.0870e-01 8.2334e-02 -3.1156e-01 1.6966e-01
#> 3 8.3261e-02 -9.1858e-02 -6.3092e-02 1.6977e-01 -1.5631e-01 -2.8049e-01
#> 4 1.6148e-01 2.7784e-01 1.1408e-01 -1.1857e-01 2.0479e-01 4.9643e-01
#> 5 2.7213e-01 1.1047e-01 -2.1958e-03 3.5385e-01 2.9398e-01 3.9062e-02
#> year
#> age 7 8 9 10
#> 1 -5.2137e-01 1.5284e-01 4.7018e-01 -3.2020e-01
#> 2 2.1607e-01 -1.5912e-01 -3.6545e-01 -4.6965e-01
#> 3 4.7265e-02 2.0275e-01 -1.4381e-01 2.4078e-01
#> 4 -3.2431e-01 4.7721e-01 -9.2953e-02 9.0610e-02
#> 5 2.3515e-01 1.8140e-01 2.0313e-01 2.7131e-01
#>
#> , , unit = 2, season = 2, area = 2
#>
#> year
#> age 1 2 3 4 5 6
#> 1 2.8748e-01 2.5721e-02 -1.0500e-01 1.1833e-01 -4.4675e-01 4.0842e-01
#> 2 -4.3708e-01 -1.5027e-01 2.3270e-01 -1.6205e-01 -1.1660e-01 4.8094e-01
#> 3 -2.9469e-01 -3.9566e-01 1.0014e-01 1.2334e-01 -5.4484e-01 -3.6306e-01
#> 4 2.6355e-01 -4.1417e-02 -2.0809e-01 -2.9005e-01 -4.5380e-02 -4.9284e-01
#> 5 8.1672e-02 -1.2236e-04 -4.5403e-02 -2.1440e-01 5.5582e-02 1.6217e-01
#> year
#> age 7 8 9 10
#> 1 -1.2720e-02 -2.2318e-01 1.4263e-01 -2.1030e-01
#> 2 -3.3004e-01 -1.5000e-01 4.2823e-02 4.8706e-01
#> 3 -2.2328e-01 -2.6071e-01 -1.7482e-01 -5.1463e-01
#> 4 -2.6761e-01 -2.4131e-02 8.0640e-02 -6.6638e-02
#> 5 -3.4958e-01 -1.5941e-01 5.6130e-02 3.9109e-02
#>
#> units: NA
dim(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 0.40061 0.47592
#>
#> 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 0.40061 0.47592
#>
#> units: NA