Generate Random Age or Age-Sex Profiles

Generate random age or age-sex profiles from an object of class "bage_ssvd". An object of class "bage_ssvd" holds results from an SVD decomposition of demographic data.

Usage

# S3 method for class 'bage_ssvd'
generate(
  x,
  v = NULL,
  n_draw = 20,
  n_comp = NULL,
  indep = NULL,
  age_labels = NULL,
  ...
)

Arguments

x

An object of class "bage_ssvd".

v

Version of data to use.

n_draw

Number of random draws to generate.

n_comp

The number of components. The default is half the total number of components of object.

indep

Whether to use independent or joint SVDs for each sex/gender, if the data contains a sex/gender variable. The default is to use independent SVDs. To obtain results for the total population when the data contains a sex/gender variable, set indep to NA.

age_labels

Age labels for the desired age or age-sex profile. If no labels are supplied, the most detailed profile available is used.

...

Unused. Included for generic consistency only.

Value

A tibble

Scaled SVDs of demographic databases in bage

• HMD Mortality rates from the Human Mortality Database.

• HFD Fertility rates from the Human Fertility Database.

• LFP Labor forcce participation rates from the OECD.

See also

• components() Components used by SVD prior.

• SVD() SVD prior for term involving age.

• SVD_AR1(), SVD_AR(), SVD_RW(), SVD_RW2() Dynamic SVD priors for terms involving age and time.

• poputils::age_labels() Generate age labels.

Examples

## females and males modeled independently
generate(HMD) 
#> # A tibble: 4,440 × 4
#>    draw   sex   age   value
#>    <fct>  <fct> <fct> <dbl>
#>  1 Draw 1 Male  0     -4.29
#>  2 Draw 1 Male  1     -7.02
#>  3 Draw 1 Male  2     -7.70
#>  4 Draw 1 Male  3     -8.04
#>  5 Draw 1 Male  4     -8.29
#>  6 Draw 1 Male  5     -8.49
#>  7 Draw 1 Male  6     -8.63
#>  8 Draw 1 Male  7     -8.75
#>  9 Draw 1 Male  8     -8.86
#> 10 Draw 1 Male  9     -8.96
#> # ℹ 4,430 more rows

## joint model for females and males
generate(HMD, indep = FALSE) 
#> # A tibble: 4,440 × 4
#>    draw   sex    age   value
#>    <fct>  <fct>  <fct> <dbl>
#>  1 Draw 1 Female 0     -4.92
#>  2 Draw 1 Female 1     -7.48
#>  3 Draw 1 Female 2     -8.05
#>  4 Draw 1 Female 3     -8.31
#>  5 Draw 1 Female 4     -8.49
#>  6 Draw 1 Female 5     -8.63
#>  7 Draw 1 Female 6     -8.72
#>  8 Draw 1 Female 7     -8.80
#>  9 Draw 1 Female 8     -8.86
#> 10 Draw 1 Female 9     -8.92
#> # ℹ 4,430 more rows

## SVD for females and males combined
generate(HMD, indep = NA)
#> # A tibble: 2,220 × 3
#>    draw   age   value
#>    <fct>  <fct> <dbl>
#>  1 Draw 1 0     -4.55
#>  2 Draw 1 1     -7.26
#>  3 Draw 1 2     -8.03
#>  4 Draw 1 3     -8.44
#>  5 Draw 1 4     -8.75
#>  6 Draw 1 5     -8.97
#>  7 Draw 1 6     -9.15
#>  8 Draw 1 7     -9.30
#>  9 Draw 1 8     -9.45
#> 10 Draw 1 9     -9.56
#> # ℹ 2,210 more rows

## specify age groups
labels <- poputils::age_labels(type = "lt", max = 60)
generate(HMD, age_labels = labels)
#> # A tibble: 560 × 4
#>    draw   sex    age   value
#>    <fct>  <fct>  <fct> <dbl>
#>  1 Draw 1 Female 0     -4.86
#>  2 Draw 1 Female 1-4   -7.48
#>  3 Draw 1 Female 5-9   -7.90
#>  4 Draw 1 Female 10-14 -7.76
#>  5 Draw 1 Female 15-19 -7.11
#>  6 Draw 1 Female 20-24 -6.95
#>  7 Draw 1 Female 25-29 -6.81
#>  8 Draw 1 Female 30-34 -6.50
#>  9 Draw 1 Female 35-39 -6.10
#> 10 Draw 1 Female 40-44 -5.66
#> # ℹ 550 more rows