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Split interval counts

Source: R/split_interval_counts.R
split_interval_counts.Rd

split_interval_counts() splits counts of a given age interval in to counts for individual years based on a given weighting. Age intervals are specified by their lower (closed) and upper (open) bounds, i.e. intervals of the form [lower, upper).

Usage

split_interval_counts(
  lower_bounds,
  upper_bounds,
  counts,
  max_upper = 100L,
  weights = NULL
)

Arguments

lower_bounds, upper_bounds

[integerish].

A pair of vectors representing the bounds of the intervals.

lower_bounds must be strictly less than upper_bounds and greater than or equal to zero.

Missing (NA) bounds are not permitted.

Double vectors will be coerced to integer.

counts

[numeric].

Vector of counts to be aggregated.

max_upper

[integerish]

Represents the maximum upper bounds permitted upon splitting the data.

Any upper bound greater than this will be replaced with this value prior to splitting.

Double vectors will be coerced to integer.

weights

[numeric]

Population weightings to apply for individual years.

If NULL (default) counts will be split evenly based on interval size.

If specified, must be of length max_upper and represent weights in the range 0:(max_upper - 1).

Value

A data frame with entries age (in years) and count.

Examples


split_interval_counts(
    lower_bounds = c(0, 5, 10),
    upper_bounds = c(5, 10, 20),
    counts = c(5, 10, 30)
)
#>    age count
#> 1    0     1
#> 2    1     1
#> 3    2     1
#> 4    3     1
#> 5    4     1
#> 6    5     2
#> 7    6     2
#> 8    7     2
#> 9    8     2
#> 10   9     2
#> 11  10     3
#> 12  11     3
#> 13  12     3
#> 14  13     3
#> 15  14     3
#> 16  15     3
#> 17  16     3
#> 18  17     3
#> 19  18     3
#> 20  19     3

split_interval_counts(
    lower_bounds = c(0, 5, 10),
    upper_bounds = c(5, 10, Inf),
    counts = c(5, 10, 30),
    max_upper = 15
)
#> Warning: `upper_bounds` greater than `max_upper` (15) have been replaced prior to splitting.
#>    age count
#> 1    0     1
#> 2    1     1
#> 3    2     1
#> 4    3     1
#> 5    4     1
#> 6    5     2
#> 7    6     2
#> 8    7     2
#> 9    8     2
#> 10   9     2
#> 11  10     6
#> 12  11     6
#> 13  12     6
#> 14  13     6
#> 15  14     6

split_interval_counts(
    lower_bounds = c(0, 5),
    upper_bounds = c(5, 10),
    counts = c(5, 10),
    max_upper =10,
    weights = 1:10
)
#>    age     count
#> 1    0 0.3333333
#> 2    1 0.6666667
#> 3    2 1.0000000
#> 4    3 1.3333333
#> 5    4 1.6666667
#> 6    5 1.5000000
#> 7    6 1.7500000
#> 8    7 2.0000000
#> 9    8 2.2500000
#> 10   9 2.5000000