This can be useful to check constrained sums, or as an intermediate step for smoothing.
groupAges( Value, Age = 1:length(Value) - 1, N = 5, shiftdown = 0, AgeN, OAnew = max(Age) )
| Value | numeric. Vector of single age counts. |
|---|---|
| Age | integer. Vector of lower bounds of single age groups. |
| N | integer. The desired width of resulting age groups. Default 5. |
| shiftdown | integer. Optionally shift age groupings down by single ages. Default 0. |
| AgeN | integer vector, otherwise calculated using |
| OAnew | integer. Value of lower bound of new open age group. |
Vector of counts in N-year age groups.
If you shift the groupings, then the first age groups may have a negative lower bound
(for example of -5). These counts would be discarded for the oscillatory version of Sprague smoothing,
for example, but they are preserved in this function. The important thing to know is that if you shift
the groups, the first and last groups will not be N years wide. For example if shiftdown is 1, the first age group is 4-ages wide. The ages themselves are not returned,
but they are the name attribute of the output count vector. Note this will also correctly group abridged ages
into equal 5-year age groups if the Age argument is explicitly given. OAnew (optional) must be less than or equal to max(Age) to have any effect.
Age <- 0:100 groupAges(pop1m_ind, N = 5)#> 0 5 10 15 20 25 30 35 #> 52360652 57419164 51947630 42231074 37514223 34546587 29917765 27558300 #> 40 45 50 55 60 65 70 75 #> 22842245 18954561 16904890 10941747 11907237 6493630 5535950 2102284 #> 80 85 90 95 100 #> 2094961 601000 421930 134360 72373groupAges(pop1m_ind, N = 5, shiftdown = 1)#> 0 4 9 14 19 24 29 34 #> 40488149 61180144 51043772 46462353 37103293 37769292 29789068 28477079 #> 39 44 49 54 59 64 69 74 #> 22995247 19260609 16817385 11340613 11956304 6678264 5558252 2204548 #> 79 84 89 94 99 #> 2099864 630492 434099 120142 93594groupAges(pop1m_ind, N = 5, shiftdown = 2)#> 0 3 8 13 18 23 28 33 #> 28606305 58749766 57901419 41370149 44922109 34463405 35589397 26237746 #> 38 43 48 53 58 63 68 73 #> 26220797 17645765 18902154 10652783 12975223 6530648 5993071 2181397 #> 78 83 88 93 98 #> 2229770 638809 468914 110427 112509groupAges(pop1m_ind, N = 5, shiftdown = 3)#> 0 2 7 12 17 22 27 32 #> 17016196 60305957 54630220 49156093 40845737 40047411 33061379 30854134 #> 37 42 47 52 57 62 67 72 #> 24470101 20069309 17965797 12189059 12435565 7386079 5846470 2569058 #> 77 82 87 92 97 #> 2172557 755143 474788 133112 118398groupAges(pop1m_ind, N = 5, shiftdown = 4)#> 0 1 6 11 16 21 26 31 #> 9544406 55784596 59761861 46962015 45271071 39210273 36881374 29289697 #> 36 41 46 51 56 61 66 71 #> 26664183 19587214 18732143 11806528 13122301 7426622 6055763 2581755 #> 76 81 86 91 96 #> 2211834 835651 473762 167976 131538groupAges(pop1m_ind, N = 5, OAnew = 80)#> 0 5 10 15 20 25 30 35 #> 52360652 57419164 51947630 42231074 37514223 34546587 29917765 27558300 #> 40 45 50 55 60 65 70 75 #> 22842245 18954561 16904890 10941747 11907237 6493630 5535950 2102284 #> 80 #> 3324624