Preview Areal Weights — aw_preview_weights • areal
Description: Provides a preview of the weight options for areal weighted interpolation. This can be useful for selecting the final specification for aw_interpolate without having to construct a pipeline of all of the subfunctions manually.

# Preview Areal Weights

Source: `R/aw_preview_weights.R`
`aw_preview_weights.Rd`

Provides a preview of the weight options for areal weighted interpolation. This can be useful for selecting the final specification for `aw_interpolate` without having to construct a pipeline of all of the subfunctions manually.

    aw_preview_weights(.data, tid, source, sid, type)

## Arguments

.data | A `sf` object that data should be interpolated to (this is referred to as the `target` elsewhere in the package).
tid | A unique identification number within `target`
source | A `sf` object with data to be interpolated
sid | A unique identification number within `source`
type | One of either `"extensive"` (if the data are spatitally extensive e.g. population counts), `"intensive"` (if the data are spatially intensive e.g. population density), or `"mixed"` (if the data include both extensive and intensive values). If `"extensive"`, the sum is returned for the interpolated value. If `"intensive"`, the mean is returned for the interpolated value. If `"mixed"`, vectors named `"extensive"` and `"intensive"` containing the relevant variable names should be specified in the dots.

## Value

A tibble with the areal weights that would be used for interpolation if `type` is either `"extensive"` or `"intensive"`. If it is mixed, two tibbles (one for `"extensive"` and one for `"intensive"`) are returned as a list.

## Examples

    aw_preview_weights(ar_stl_wards, tid = WARD, source = ar_stl_race, sid = GEOID,
                       type = "extensive")#> # A tibble: 106 x 3
    #>    GEOID       extensiveSum extensiveTotal
    #>    <chr>              <dbl>          <dbl>
    #>  1 29510101100            1          0.999
    #>  2 29510101200            1          1.00
    #>  3 29510101300            1          1.00
    #>  4 29510101400            1          1.00
    #>  5 29510101500            1          0.998
    #>  6 29510101800            1          0.978
    #>  7 29510102100            1          0.991
    #>  8 29510102200            1          0.999
    #>  9 29510102300            1          0.999
    #> 10 29510102400            1          1.00
    #> # … with 96 more rows
    aw_preview_weights(ar_stl_wards, tid = WARD, source = ar_stl_asthma, sid = GEOID,
                       type = "intensive")#> # A tibble: 28 x 2
    #>     WARD intensive
    #>    <int>     <dbl>
    #>  1     1      1.00
    #>  2     2      1
    #>  3     3      1
    #>  4     4      1
    #>  5     5      1
    #>  6     6      1
    #>  7     7      1.00
    #>  8     8      1
    #>  9     9      1
    #> 10    10      1
    #> # … with 18 more rows