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     -2.34
#>  2 Draw 1 Male  1     -4.14
#>  3 Draw 1 Male  2     -4.93
#>  4 Draw 1 Male  3     -5.40
#>  5 Draw 1 Male  4     -5.78
#>  6 Draw 1 Male  5     -6.07
#>  7 Draw 1 Male  6     -6.30
#>  8 Draw 1 Male  7     -6.53
#>  9 Draw 1 Male  8     -6.76
#> 10 Draw 1 Male  9     -6.94
#> # 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     -3.02
#>  2 Draw 1 Female 1     -4.91
#>  3 Draw 1 Female 2     -5.75
#>  4 Draw 1 Female 3     -6.26
#>  5 Draw 1 Female 4     -6.64
#>  6 Draw 1 Female 5     -6.94
#>  7 Draw 1 Female 6     -7.22
#>  8 Draw 1 Female 7     -7.48
#>  9 Draw 1 Female 8     -7.69
#> 10 Draw 1 Female 9     -7.87
#> # 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     -4.18
#>  2 Draw 1 1     -6.30
#>  3 Draw 1 2     -6.80
#>  4 Draw 1 3     -7.06
#>  5 Draw 1 4     -7.23
#>  6 Draw 1 5     -7.35
#>  7 Draw 1 6     -7.44
#>  8 Draw 1 7     -7.52
#>  9 Draw 1 8     -7.58
#> 10 Draw 1 9     -7.62
#> # 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     -2.76
#>  2 Draw 1 Female 1-4   -4.55
#>  3 Draw 1 Female 5-9   -4.67
#>  4 Draw 1 Female 10-14 -4.57
#>  5 Draw 1 Female 15-19 -4.20
#>  6 Draw 1 Female 20-24 -4.13
#>  7 Draw 1 Female 25-29 -3.98
#>  8 Draw 1 Female 30-34 -3.71
#>  9 Draw 1 Female 35-39 -3.37
#> 10 Draw 1 Female 40-44 -3.02
#> # ℹ 550 more rows